MPEG news: a report from the 154th meeting

This version of the blog post is also available at ACM SIGMM Records

MPEG News Archive 

The 154th MPEG meeting took place in Santa Eulària, Spain, from April 27 to May 1, 2026. The official MPEG press release can be found here. This report highlights key outcomes from the meeting, with a focus on research directions relevant to the ACM SIGMM community:

• Exploration on MPEG Gaussian Splat Coding (GSC)
• Draft Joint Call for Proposals: Video Compression Beyond VVC
• Energy-aware Streaming in MPEG-DASH
• MPEG-AI: Vision and Scenarios for Artificial Intelligence in Multimedia
• MPEG Roadmap

Exploration on MPEG Gaussian Splat Coding (GSC)

The MPEG WG 2 Technical Requirements group — jointly with WG 4 (Video Coding), WG 5 (JVET: Joint Video Coding Team(s) with ITU-T SG 16), and WG 7 (Coding of 3D Graphics and Haptics) — made progress toward standardizing Gaussian Splat Coding (GSC) regarding draft requirements and use cases subject to change. Gaussian splatting, first introduced in a landmark 2023 ACM SIGGRAPH paper by Kerbl et al., represents 3D scenes as collections of anisotropic Gaussian primitives carrying geometry (x, y, z positions) and appearance attributes (opacity, scale, rotation, and spherical harmonics coefficients for view-dependent color), enabling photorealistic novel-view synthesis with real-time rendering. Because raw Gaussian splat data can be extremely large and the ecosystem of proprietary formats (.ply, .splat, .spz, etc.) is fragmented, MPEG has identified a clear need for interoperable, efficient compression standards. Two exploration tracks are currently being pursued: I-3DGS, which operates on Gaussian splats in the well-established “INRIA” format as a symmetric encode/decode pipeline, and A-3DGS, which allows alternative learned representations and training-integrated approaches.

The draft requirements, still evolving, currently cover representation, coding, and system aspects across both tracks, with an additional lightweight profile targeting resource-constrained devices such as mobile phones (Snapdragon 8 Gen 3/Elite) and HMDs (Snapdragon XR Gen2, e.g., Meta Quest 3). Among the coding requirements under consideration are lossy and lossless compression with variable bitrate, spatial and temporal random access, progressive and scalable decoding (quality, Level of Detail (LoD), attribute subsets), and error resilience. Notably, a lightweight profile currently proposes hard complexity constraints (i.e., real-time encode/decode on 2024/2025 mobile hardware, a 2GB runtime memory cap, and at most four concurrent video decoder sessions) reflecting MPEG’s intent to enable a fast-deployment path for interoperable interchange and storage of static Gaussian splat assets. Alongside the requirements, a draft set of 27 use cases has been identified, spanning consumer XR (telepresence, gaming, social media, retail), professional media (movie production, sports broadcasting, immersive journalism), industrial applications (digital twins, Building Information Modeling (BIM), structure inspection, disaster assessment), and emerging hybrid representations such as Gaussian splats attached to deformable meshes for avatar animation and rigging. Several of these use cases are motivating draft requirements around primitive ordering preservation and stable identifier signaling for external metadata associations, though the details of these provisions may still change.

Research aspects: Even at this early draft stage, the direction of MPEG’s GSC work opens a rich set of research opportunities. On the compression side, the dual-track structure raises open questions around rate-distortion-complexity optimization for both geometry-based and video-codec-based pipelines, including temporally coherent coding of dynamic (tracked and non-tracked) Gaussian sequences and attribute-group-aware progressive coding. The QoE angle is equally pressing: no widely accepted perceptual quality metric yet exists for 6DoF Gaussian splat rendering, and the community can contribute splat-artifact-aware metrics, view-consistency measures, and subjective evaluation methodologies. The envisioned lightweight profile points to a need for co-design of decoders and real-time renderers targeting mobile GPU architectures, offering opportunities in GPU-friendly bitstream layouts and LOD-driven streaming. From a systems and networking perspective, the spatial and temporal random-access provisions, combined with the breadth of use cases demanding adaptive streaming to diverse devices (HMDs, phones, TVs, browsers), map naturally onto adaptive bitrate research, ROI- and view-dependent segment delivery, and loss-resilient transmission of splat parameters. Finally, the emerging use cases around hybrid mesh-Gaussian avatars, scene editing, and semantic metadata associations introduce new multimedia content management and interactive media challenges that go well beyond traditional video streaming and are squarely within the scope of ACM SIGMM’s research community.

Draft Joint Call for Proposals: Video Compression Beyond VVC

MPEG’s Joint Video Experts Team (JVET) — operating jointly under ITU-T SG21 and ISO/IEC JTC 1/SC 29 — advanced a draft Joint Call for Proposals (CfP) for a new generation of video compression technology with capabilities that would substantially exceed those of the current Versatile Video Coding (VVC) standard (Rec. ITU-T H.266 | ISO/IEC 23090-3). The final CfP is planned for July 2026, with proposal submissions evaluated at a JVET meeting in January 2027 and a tentative target of a completed standard by October 2029. The overarching goal is to solicit compression technology that significantly improves upon VVC’s Main 10 Profile in terms of rate-distortion performance, encoder/decoder implementability, applicability to diverse content types, and additional features such as low latency, error robustness, and scalability, while explicitly recognizing that practical fast encoding is increasingly important across a growing range of applications.

The draft CfP defines four test cases. The primary test case targets improved compression without runtime constraints, spanning several content categories: SDR random-access at UHD/4K and HD resolutions, SDR low-delay HD (targeting conversational and gaming applications), HDR content under both PQ and HLG transfer functions at UHD, gaming low-delay HD, and user-generated content. Three additional test cases impose encoder runtime constraints relative to the VVC Test Model (VTM) reference encoder, enabling JVET to characterize the compression-versus-speed trade-off across submissions. Formal subjective evaluation will follow the degradation category rating (DCR) methodology per ITU-R BT.500. Importantly, the CfP explicitly addresses neural and learned components: proponents must disclose what training data was used and are prohibited from using any test sequence as training material, and source code (incl. training scripts or parameter derivation procedures) must be made available for accepted technologies entering the core experiments process. The draft notes that specific test sequences and target bitrates may still change before the final CfP is issued.

Research aspects: The runtime-constrained test cases create a natural framework for studying the compression-complexity Pareto frontier for both classical and learned codecs. The inclusion of user-generated content and gaming video as distinct categories invites research into content-adaptive coding tools and perceptual quality metrics tailored to these sources, as does the HDR coverage with its use of weighted PSNR alongside MS-SSIM. The explicit allowance for neural and learned components, with mandatory training data disclosure and source code requirements, signals that JVET anticipates hybrid and end-to-end learned codecs as serious contenders, making codec-agnostic adaptive streaming, QoE modeling for learned video codecs, and large-scale perceptual quality benchmarking timely topics for the ACM SIGMM community.

Energy-aware Streaming in MPEG-DASH

MPEG’s WG 3 (Systems/DASH) is developing a framework for integrating energy-related information into adaptive streaming workflows, currently documented as a Technology under Consideration (TuC) in the DASH specification. The proposed framework treats energy as a first-class design metric alongside QoE, latency, and throughput, and defines an end-to-end approach for assigning, aggregating, and propagating energy consumption data across the entire media delivery chain — from production and encoding through CDN distribution to the client. A key design principle is extensibility: rather than hardcoding specific metrics, the framework proposes a common registry of energy-related metrics (such as energy indices or carbon indices) identified via URNs or 4CC codes, inspired by existing registries like MP4RA and DASH-IF. Energy information may be carried through a variety of existing DASH mechanisms, including MPD descriptors at multiple granularity levels (Adaptation Set, Representation, Segment, Service Location), CMCD/CMSD extensions, metadata tracks, SAND messages, and event streams. A dedicated Energy descriptor in the MPD is proposed, analogous to existing Accessibility descriptors, to expose energy information to clients and applications for representation selection, user exposure, and reporting to back-end servers.

Concept of Energy-aware Streaming in MPEG-DASH.

The April 2026 update reported significant progress on two related fronts. A 5G-MAG workshop co-organized with 3GPP SA4 and Greening of Streaming (March 2026) highlighted growing industry consensus around practical energy measurement, surfacing findings such as the dominant role of device eco-mode settings and content brightness over codec or resolution choices in determining end-device energy consumption, and the challenge of reproducible cloud-based energy measurement. In parallel, 3GPP’s Rel-20 study on media energy consumption exposure (FS_Energy_Ph2_MED) reached 80% completion and is expected to conclude in June 2026, with normative work to follow. Notably, 3GPP’s current draft conclusions focus on generic architectural enablers, specifically a new Energy Information Application Function, while explicitly deferring media-layer and client-driven energy optimization to external bodies such as MPEG, SVTA, and DVB. This positions MPEG-DASH’s manifest-based energy signaling work as the natural venue for maturing the streaming-level mechanisms that 3GPP may later reference.

Research aspects: This work opens several timely directions. Energy-aware ABR algorithm design, i.e., jointly optimizing QoE and energy across representation selection, CDN choice, and client device settings, is a natural extension of the existing adaptive streaming research agenda. The proposed metrics registry and MPD-level signaling create opportunities for dataset construction and benchmarking, building on emerging open datasets such as COCONUT and VEED. The finding that device-side factors (eco-mode, display brightness) dominate energy consumption over codec and bitrate choices challenges some common assumptions and calls for more holistic QoE-energy modeling. Finally, the cross-SDO coordination between MPEG, 3GPP, IETF (GREEN working group), and Greening of Streaming presents opportunities for the ACM SIGMM community to contribute to the design of interoperable, standardized energy reporting APIs for streaming services.

MPEG-AI: Vision and Scenarios for Artificial Intelligence in Multimedia

The first edition of ISO/IEC TR 23888-1 serves as the foundational vision document for the MPEG-AI series (ISO/IEC 23888). The document maps out how AI and neural network technologies interact with multimedia standardization along two complementary axes: (i) AI as a multimedia coding tool (e.g., AI-based video compression, 3D point cloud coding) and (ii) multimedia as input for AI consumption (e.g., video coding optimized for machine vision tasks). Under this umbrella, the document surveys six technical areas. In AI-based video coding, neural network components are explored as hybrid additions to VVC-style codecs, covering in-loop filters, intra prediction, super-resolution via reference picture resampling, and content-adaptive postfilters transmitted via SEI messages using the Neural Network Coding standard (NNC, ISO/IEC 15938-17). In AI-based 3D graphics coding, the focus is on dynamic point clouds for immersive (XR, gaming) and machine-oriented (autonomous navigation, BIM) applications, where sparsity and geometric irregularity pose unique challenges beyond those faced by image/video AI codecs. AI model compression (NNC) addresses the bandwidth-efficient deployment and incremental updating of neural network weights to devices, with use cases ranging from adaptive streaming ABR models to federated learning and postfilter delivery. Video coding for machines (VCM) targets compression optimized for downstream AI tasks such as object detection, tracking, and content moderation, with applications in surveillance, intelligent transportation, smart cities, and industrial inspection. Feature coding for machines (FCM) extends this to split-inference architectures where intermediate feature maps — rather than reconstructed video — are compressed and transmitted between edge devices and servers. Finally, distributed AI media description addresses the interoperable representation and API-level exchange of AI inference results (e.g., bounding boxes, segmentation masks) between networked media analyzers, as specified in the MPEG-IoMT suite.

ISO/IEC TR 23888-1: AI as a multimedia coding tool and multimedia as input for AI consumption.

Research aspects: The hybrid codec paradigm raises open questions around joint optimization of traditional and learned tools and complexity-aware training for mobile targets. The VCM and FCM tracks call for new task-oriented quality metrics capturing machine-task performance as a function of bitrate, an area where the multimedia and computer vision communities can collaborate. The split-inference and feature coding scenarios introduce latency-constrained compression problems for edge-to-cloud pipelines, which naturally connect to adaptive streaming and IoT research. Finally, the reproducibility and bit-exactness challenges highlighted in the document — hardware-dependent inference, non-deterministic training, and the absence of standardized evaluation environments — present an opportunity for the community to develop shared benchmarking infrastructure for learned multimedia codecs.

MPEG Roadmap

MPEG released an updated roadmap at its 154th meeting, reflecting the current status and near-term trajectory of its standardization activities across three broad pillars. Under Media Coding, work nearing completion includes MPEG Immersive Video v.2, Feature Coding for Machines, Solid Point Cloud Coding, and Dynamic Mesh Compression, while longer-horizon efforts cover AI Graphics Compression, Video Coding for Machines, Lenslet video coding, and — directly relevant to this report — both Video-based and Geometry-based Gaussian Splat Coding tracks. Under Systems and Tools, near-term deliverables include DASH v.7, Green metadata v.4, and Carriage of Haptics Data, with CMAF v.4 and File Format (ISOBMFF) v.10 on a slightly longer timeline. The Beyond Media pillar continues to advance genomic data search and biomedical waveform coding (BWC), alongside media authenticity and provenance indication — underscoring MPEG’s expanding scope well beyond traditional audiovisual applications.

MPEG Roadmap as of April 2026.

Research aspects: The roadmap highlights several intersecting research opportunities. The convergence of volumetric and neural representations (i.e., point clouds, dynamic meshes, Gaussian splats, and lenslet video; all progressing in parallel) raises open questions around unified rate-distortion frameworks and cross-format QoE evaluation for 6DoF experiences. The simultaneous progression of Video Coding for Machines and Feature Coding for Machines alongside traditional human-centric codecs calls for research into adaptive pipelines that can serve both human and machine consumers from a shared bitstream. The Green metadata track connects directly to the energy-aware streaming work discussed above, underscoring the need for end-to-end energy modeling that spans codec choice, packaging, delivery, and consumption. Finally, the Beyond Media thread (e.g., particularly genomic data and biomedical waveforms) signals an expanding definition of “multimedia” that the ACM SIGMM community may wish to engage with as compression, retrieval, and QoE methods developed for audiovisual content find applicability in life sciences.

Concluding Remarks

The 154th MPEG meeting in Santa Eularia reflects a standards body in active transition, broadening its scope from traditional audiovisual compression toward a richer landscape that encompasses neural scene representations, AI-native codecs, energy-aware delivery, and even biomedical data. The Gaussian Splat Coding exploration, the next-generation video compression Call for Proposals, the MPEG-AI vision document, and the energy-aware streaming framework each address distinct but interconnected challenges: how to represent, compress, deliver, and consume increasingly complex and diverse media efficiently and sustainably. For the ACM SIGMM community, this meeting offers both a map of where industry standardization is heading and a set of open research problems (i.e., spanning perceptual quality assessment, learned compression, edge inference, green streaming, and immersive media delivery) where academic contributions can meaningfully shape the next generation of multimedia standards.

The 155th MPEG meeting will be held in Geneva, Switzerland, from July 13 to 17, 2026. Click here for more information about MPEG meetings and ongoing developments.

Sustainability in Video Encoding and Streaming

Sustainability in Video Encoding and Streaming:

Energy-Efficient Techniques and Metrics

Workshop on Media Energy Consumption Measurement and Exposure

[Workshop URL] [Slides] [PDF]

Presenter: Christian Timmerer (Alpen-Adria-Universität Klagenfurt)

Abstract: The presentation discusses the increasing environmental impact of video streaming and highlights the urgent need for more sustainable approaches across the entire streaming pipeline. Video traffic dominates internet usage and contributes significantly to global greenhouse gas emissions, while the demand for higher quality content continues to drive up computational complexity and energy consumption in encoding, delivery, and playback.

A central insight is that there is a strong trade-off between video quality and energy consumption, where small reductions in quality can lead to substantial energy savings. By introducing energy as an explicit optimization objective, techniques such as content-aware encoding, energy-aware bitrate ladder construction, and real-time optimization for live streaming can significantly reduce energy usage while maintaining nearly the same perceptual quality.

The work also emphasizes the role of adaptive bitrate algorithms that incorporate energy consumption alongside traditional quality and buffer-based metrics. These approaches demonstrate that it is possible to simultaneously improve user experience and reduce energy consumption, indicating that sustainability and performance can be aligned rather than conflicting goals.

To enable such optimizations, the presentation introduces a range of metrics and models, including video complexity measures, quality prediction models, and machine learning-based approaches for estimating encoding and decoding energy as well as CO₂ emissions. These tools support more informed, data-driven decisions across the full streaming workflow from encoding to playback.

Another important theme is end-to-end optimization, where energy efficiency depends on the combined behavior of encoding strategies, bitrate selection, and client-side adaptation. Industry efforts confirm the practical relevance of these approaches and highlight the importance of collaboration and real-world validation.

Despite promising results, several challenges remain, including difficulties in measuring and benchmarking energy consumption, the lack of standardized methodologies, and the limited integration of energy considerations into existing workflows. Overall, the presentation argues that energy consumption should become a first-class optimization target in video streaming systems, similar to established quality metrics, to enable truly sustainable media delivery.

Keywords: sustainable streaming, energy-aware encoding, adaptive bitrate streaming, green multimedia, video compression, bitrate ladder optimization, QoE optimization, energy-quality tradeoff, video complexity analysis, CO2 footprint, energy modeling, machine learning for video, end-to-end optimization, eco-efficient streaming, real-time streaming optimization

MPEG news: a report from the 153rd meeting

This version of the blog post is also available at ACM SIGMM Records

MPEG News Archive

The 153rd MPEG meeting took place online from January 19-23, 2026. The official MPEG press release can be found here. This report highlights key outcomes from the meeting, with a focus on research directions relevant to the ACM SIGMM community:

• MPEG Roadmap
• Exploration on MPEG Gaussian Splat Coding (GSC)
• MPEG Immersive Video 2nd edition (new white paper)

MPEG Roadmap

MPEG released an updated roadmap showing continued convergence of immersive and “beyond video” media with deployment-ready systems work. Near-term priorities include 6DoF experiences (MPEG Immersive Video v2 and 6DoF audio), volumetric representations (dynamic meshes, solid point clouds, LiDAR, and emerging Gaussian splat coding), and “coding for machines,” which treats visual and audio signals as inputs to downstream analytics rather than only for human consumption.

Research aspects: The most promising research opportunities sit at the intersections: renderer and device-aware rate-distortion-complexity optimization for volumetric content; adaptive streaming and packaging evolution (e.g., MPEG-DASH / CMAF) for interactive 6DoF services under tight latency constraints; and cross-cutting themes such as media authenticity and provenance, green and energy metadata, and exploration threads on neural-network-based compression and compression of neural networks that foreshadow AI-native multimedia pipelines.

MPEG Gaussian Splat Coding (GSC)

Gaussian Splat Coding (GSC) is MPEG’s effort to standardize how 3D Gaussian Splatting content, scenes represented as sparse “Gaussian splats” with geometry plus rich attributes (scale and rotation, opacity, and spherical-harmonics appearance for view-dependent rendering), is encoded, decoded, and evaluated so it can be exchanged and rendered consistently across platforms. The main motivation is interoperability for immersive media pipelines: enabling reproducible results, shared benchmarks, and comparable rate-distortion-complexity trade-offs for use cases spanning telepresence and immersive replay to mobile XR and digital twins, while retaining the visual strengths that made 3DGS attractive compared to heavier neural scene representations.

The work remains in an exploration phase, coordinated across ISO/IEC JTC 1/SC 29 groups WG 4 (MPEG Video Coding) and WG 7 (MPEG Coding for 3D Graphics and Haptics) through Joint Exploration Experiments covering datasets and anchors, new coding tools, software (renderer and metrics), and Common Test Conditions (CTC). A notable systems thread is “lightweight GSC” for resource-constrained devices (single-frame, low-latency tracks using geometry-based and video-based pipelines with explicit time and memory targets), alongside an “early deployment” path via amendments to existing MPEG point-cloud codecs to more natively carry Gaussian-splat parameters. In parallel, MPEG is testing whether splat-specific tools can outperform straightforward mappings in quality, bitrate, and compute for real-time and streaming-centric scenarios.

Research aspects: Relevant SIGMM directions include splat-aware compression tools and rate-distortion-complexity optimization (including tracked vs. non-tracked temporal prediction); QoE evaluation for 6DoF navigation (metrics for view and temporal consistency and splat-specific artifacts); decoder and renderer co-design for real-time and mobile lightweight profiles (progressive and LOD-friendly layouts, GPU-friendly decode); and networked delivery problems such as adaptive streaming, ROI and view-dependent transmission, and loss resilience for splat parameters. Additional opportunities include interoperability work on reproducible benchmarking, conformance testing, and practical packaging and signaling for deployment.

MPEG Immersive Video 2nd edition (white paper)

The second edition of MPEG Immersive Video defines an interoperable bitstream and decoding process for efficient 6DoF immersive scene playback, supporting translational and rotational movement with motion parallax to reduce discomfort often associated with pure 3DoF viewing. The second edition primarily extends functionality (without changing the high-level bitstream structure), adding capabilities such as capture-device information, additional projection types, and support for Simple Multi-Plane Image (MPI), alongside tools that better support geometry and attribute handling and depth-related processing.

Architecturally, MIV ingests multiple (unordered) camera views with geometry (depth and occupancy) and attributes (e.g., texture), then reduces inter-view redundancy by extracting patches and packing them into 2D “atlases” that are compressed using conventional video codecs. MIV-specific metadata signals how to reconstruct views from the atlases. The standard is built as an extension of the common Visual Volumetric Video-based Coding (V3C) bitstream framework shared with V-PCC, with profiles that preserve backward compatibility while introducing a new profile for added second-edition functionality and a tailored profile for full-plane MPI delivery.

Research aspects: Key SIGMM topics include systems-efficient 6DoF delivery (better view and patch selection and atlas packing under latency and bandwidth constraints); rate-distortion-complexity-QoE optimization that accounts for decode and render cost (especially on HMD and mobile) and motion-parallax comfort; adaptive delivery strategies (representation ladders, viewport and pose-driven bit allocation, robust packetization and error resilience for atlas video plus metadata); renderer-aware metrics and subjective protocols for multi-view temporal consistency; and deployment-oriented work such as profile and level tuning, codec-group choices (HEVC / VVC), conformance testing, and exploiting second-edition features (capture device info, depth tools, Simple MPI) for more reliable reconstruction and improved user experience.

Concluding Remarks

The meeting outcomes highlight a clear shift toward immersive and AI-enabled media systems where compression, rendering, delivery, and evaluation must be co-designed. These developments offer timely opportunities for the ACM SIGMM community to contribute reproducible benchmarks, perceptual metrics, and end-to-end streaming and systems research that can directly influence emerging standards and deployments.

The 154th MPEG meeting will be held in Santa Eulària, Spain, from April 27 to May 1, 2026. Click here for more information about MPEG meetings and ongoing developments.

Professor of Information Systems Engineering (all genders welcome)

Department of Informatics Systems  

Full professorships  | Full time

Application deadline:  22 March 2026

Reference code: 43/02-PERS/26

URL: https://jobs.aau.at/en/job/professor-of-information-systems-engineering-all-genders-welcome/

Announcement

The University of Klagenfurt wants to attract more women for professorships.

We are pleased to announce the following open position at the Department of Informatics Systems, Faculty of Technical Sciences, in compliance with the provisions of § 98 (permanent) or § 98 (fixed-term, max. 6 years) of the Austrian Universities Act:

Professor of Information Systems Engineering (all genders welcome)

This is a full-time position available from 1 October 2027. Depending on the candidate’s academic credentials, the employment contract can be concluded either as a permanent employment contract or as a fixed-term employment contract with the option of a permanent extension. The duration of fixed-term contracts is subject to negotiation.

With approximately 13,000 students, the University of Klagenfurt is a young, vibrant and innovative university, located at the intersection of Alpine and Mediterranean culture in an area that offers exceptionally high quality of life. As a public university pursuant to § 6 of the Austrian Universities Act, it receives federal funding. The university operates under the motto “Beyond Boundaries!”.

In accordance with its key strategic road map, the Development Plan, the university’s primary guiding principles and objectives include the pursuit of scientific excellence regarding the appointment of professors, favourable research conditions, a good faculty-student ratio, and the promotion of the development of early career researchers.

Information Systems Engineering focuses on the design, development, and management of large systems that connect people, data, and technology to support organizational goals. It combines principles of software engineering, data management, business processes, and emerging digital technologies to create solutions that enhance decision-making, optimize operations, and drive innovation.

We welcome applications addressing the engineering of Information Systems, in particular those focusing on designing, modelling, executing, verifying, and optimizing business processes. We are looking for a highly qualified and internationally visible scientist with high engagement in developing and sustaining an ambitious and innovative research and teaching programme. Candidates should also be interested in developing collaborations in the university’s Areas of Research Strength: Digitalisation and Health, Multiple Perspectives in Optimization, Networked and Autonomous Systems and/or the Cluster of Excellence “Bilateral AI”.

Your responsibilities – what awaits you

The duties of the position include:

• Representing the field of Information Systems Engineering in research and teaching
• Teaching in relevant degree programmes at Bachelor’s, Master’s, and Doctoral level both in English and German, as well as supervision of student projects and academic theses
• Advising and mentoring of students and early career researchers
• Competitive research grant acquisition and management
• Collaboration with academic and industry partners
• Participation in university management
• Participation in third mission and public relations activities

Your profile

• Habilitation or equivalent qualification in Computer Science or a relevant neighbouring field
• Excellent research track record in Information Systems Engineering
• Experience in the acquisition and management of competitive third-party funded research projects of a relevant volume
• Teaching competence and experience at university level
• Experience in the (co-)supervision of academic theses
• Fluency in English

This distinguishes you additionally

• Interdisciplinary experience
• Scientific dissemination skills
• Engagement in academic administrative duties
• Competence in leadership and teamwork
• Competence in gender mainstreaming and diversity management

German language skills are not a formal prerequisite, but proficiency at level B2 is expected within two years.

Why you will enjoy working with us

The salary is subject to negotiation. The minimum gross salary for the position at this level (salary group A1 for University Staff according to the Austrian Universities’ Collective Bargaining Agreement) is currently € 93,986 per year.

The university is committed to increasing the number of women among the faculty, particularly in high-level positions, and therefore specifically invites applications from qualified women. Among equally qualified candidates, women will receive preferential consideration.

People with disabilities or chronic diseases who meet the qualification criteria are explicitly invited to apply.

In accordance with the Austrian Income Tax Act, an attractive relocation tax allowance can be granted for the first five years in the case of appointments to professorships in Austria. The prerequisites are subject to examination on a case by case basis.

Please submit your application in English by e-mail to the University of Klagenfurt, Office of the Senate, attn. Mag.a (FH) Sabine Seebacher via application_professorship@aau.at no later than 22 March, 2026, including:

• a mandatory principal part not exceeding five pages (https://jobs.aau.at/wp-content/uploads/specimen_main_part_application_professorship.docx). The submission of the mandatory principal part constitutes a necessary condition for the validity of your application.
• one single PDF including:
• a letter of motivation
• a detailed scientific CV
• a comprehensive list of publications, talks, and of all courses taught
• a list of projects that you acquired as a PI or co-PI, including the amount of funding that was attributed to you
• a research statement
• a teaching statement
• supplementary documents where applicable (e.g., course evaluations)
• links to publicly available versions of your three most important publications within the scope of this professorship

For general information, please refer to the general information provided at https://jobs.aau.at/en/the-university-as-employer/. For specific information about the position, please contact Prof. Dr. Martin Pinzger (Tel.: +43 463 2700 3513; martin.pinzger@aau.at).

MPEG news: a report from the 152nd meeting

 This version of the blog post is also available at ACM SIGMM Records

MPEG News Archive

The 152nd MPEG meeting took place in Geneva, Switzerland, from October 7 to October 11, 2025. The official MPEG press release can be found here. This column highlights key points from the meeting, amended with research aspects relevant to the ACM SIGMM community:

• MPEG Systems received an Emmy® Award for the Common Media Application Format (CMAF). A separate press release regarding this achievement is available here.
• JVET ratified new editions of VSEI, VVC, and HEVC
• The fourth edition of Visual Volumetric Video-based Coding (V3C and V-PCC) has been finalized
• Responses to the call for evidence on video compression with capability beyond VVC successfully evaluated

MPEG Systems received an Emmy® Award for the Common Media Application Format (CMAF)

On September 18, 2025, the National Academy of Television Arts & Sciences (NATAS) announced that the MPEG Systems Working Group (ISO/IEC JTC 1/SC 29/WG 3) had been selected as a recipient of a Technology & Engineering Emmy® Award for standardizing the Common Media Application Format (CMAF). But what is CMAF? CMAF (ISO/IEC 23000-19) is a media format standard designed to simplify and unify video streaming workflows across different delivery protocols and devices. Here’s a structured overview. Before CMAF, streaming services often had to produce multiple container formats, i.e., (i) ISO Base Media File Format (ISOBMFF) for MPEG-DASH and MPEG-2 Transport Stream (TS) for Apple HLS. This duplication resulted in additional encoding, packaging, and storage costs. I wrote a blog post about this some time ago here. CMAF’s main goal is to define a single, standardized segmented media format usable by both HLS and DASH, enabling “encode once, package once, deliver everywhere.”

The core concept of CMAF is that it is based on ISOBMFF, the foundation for MP4. Each CMAF stream consists of a CMAF header, CMAF media segments, and CMAF track files (a logical sequence of segments for one stream, e.g., video or audio). CMAF enables low-latency streaming by allowing progressive segment transfer, adopting chunked transfer encoding via CMAF chunks. CMAF defines interoperable profiles for codecs and presentation types for video, audio, and subtitles. Thanks to its compatibility with and adoption within existing streaming standards, CMAF bridges the gaps between DASH and HLS, creating a unified ecosystem.

Research aspects include – but are not limited to – low-latency tuning (segment/chunk size trade-offs, HTTP/3, QUIC), Quality of Experience (QoE) impact of chunk-based adaptation, synchronization of live and interactive CMAF streams, edge-assisted CMAF caching and prediction, and interoperability testing and compliance tools.

JVET ratified new editions of VSEI, VVC, and HEVC

At its 40th meeting, the Joint Video Experts Team (JVET, ISO/IEC JTC 1/SC 29/WG 5) concluded the standardization work on the next editions of three key video coding standards, advancing them to the Final Draft International Standard (FDIS) stage. Corresponding twin-text versions have also been submitted to ITU-T for consent procedures. The finalized standards include:

• Versatile Supplemental Enhancement Information (VSEI) — ISO/IEC 23002-7 | ITU-T Rec. H.274
• Versatile Video Coding (VVC) — ISO/IEC 23090-3 | ITU-T Rec. H.266
• High Efficiency Video Coding (HEVC) — ISO/IEC 23008-2 | ITU-T Rec. H.265

The primary focus of these new editions is the extension and refinement of Supplemental Enhancement Information (SEI) messages, which provide metadata and auxiliary data to support advanced processing, interpretation, and quality management of coded video streams.

The updated VSEI specification introduces both new and refined SEI message types supporting advanced use cases:

• AI-driven processing: Extensions for neural-network-based post-filtering and film grain synthesis offer standardized signalling for machine learning components in decoding and rendering pipelines.
• Semantic and multimodal content: New SEI messages describe infrared, X-ray, and other modality indicators, region packing, and object mask encoding; creating interoperability points for multimodal fusion and object-aware compression research.
• Pipeline optimization: Messages defining processing order and post-processing nesting support research on joint encoder-decoder optimization and edge-cloud coordination in streaming architectures.
• Authenticity and generative media: A new set of messages supports digital signature embedding and generative-AI-based face encoding, raising questions for the SIGMM community about trust, authenticity, and ethical AI in media pipelines.
• Metadata and interpretability: New SEIs for text description, image format metadata, and AI usage restriction requests could facilitate research into explainable media, human-AI interaction, and regulatory compliance in multimedia systems.

All VSEI features are fully compatible with the new VVC edition, and most are also supported in HEVC. The new HEVC edition further refines its multi-view profiles, enabling more robust 3D and immersive video use cases.

Research aspects of these new standard’s editions can be summarized as follows: (i) Define new standardized interfaces between neural post-processing and conventional video coding, fostering reproducible and interoperable research on learned enhancement models. (ii) Encourage exploration of metadata-driven adaptation and QoE optimization using SEI-based signals in streaming systems. (iii) Open possibilities for cross-layer system research, connecting compression, transport, and AI-based decision layers. (iv) Introduce a formal foundation for authenticity verification, content provenance, and AI-generated media signalling, relevant to current debates on trustworthy multimedia.

These updates highlight how ongoing MPEG/ITU standardization is evolving toward a more AI-aware, multimodal, and semantically rich media ecosystem, providing fertile ground for experimental and applied research in multimedia systems, coding, and intelligent media delivery.

The fourth edition of Visual Volumetric Video-based Coding (V3C and V-PCC) has been finalized

MPEG Coding of 3D Graphics and Haptics (ISO/IEC JTC 1/SC 29/WG7) has advanced MPEG-I Part 5 – Visual Volumetric Video-based Coding (V3C and V-PCC) to the Final Draft International Standard (FDIS) stage, marking its fourth edition. This revision introduces major updates to the Video-based Coding of Volumetric Content (V3C) framework, particularly enabling support for an additional bitstream instance: V-DMC (Video-based Dynamic Mesh Compression).

Previously, V3C served as the structural foundation for V-PCC (Video-based Point Cloud Compression) and MIV (MPEG Immersive Video). The new edition extends this flexibility by allowing V-DMC integration, reinforcing V3C as a generic, extensible framework for volumetric and 3D video coding. All instances follow a shared principle, i.e., using conventional 2D video codecs (e.g., HEVC, VVC) for projection-based compression, complemented by specialized tools for mapping, geometry, and metadata handling.

While V-PCC remains co-specified within Part 5, MIV (Part 12) and V-DMC (Part 29) are standardized separately. The progression to FDIS confirms the technical maturity and architectural stability of the framework.

This evolution opens new research directions as follows: (i) Unified 3D content representation, enabling comparative evaluation of point cloud, mesh, and view-based methods under one coding architecture. (ii) Efficient use of 2D codecs for 3D media, raising questions on mapping optimization, distortion modeling, and geometry-texture compression. (iii) Dynamic and interactive volumetric streaming, relevant to AR/VR, telepresence, and immersive communication research.

The fourth edition of MPEG-I Part 5 thus positions V3C as a cornerstone for future volumetric, AI-assisted, and immersive video systems, bridging standardization and cutting-edge multimedia research.

Responses to the call for evidence on video compression with capability beyond VVC successfully evaluated

The Joint Video Experts Team (JVET, ISO/IEC JTC 1/SC 29/WG 5) has completed the evaluation of submissions to its Call for Evidence (CfE) on video compression with capability beyond VVC. The CfE investigated coding technologies that may surpass the performance of the current Versatile Video Coding (VVC) standard in compression efficiency, computational complexity, and extended functionality.

A total of five submissions were assessed, complemented by ECM16 reference encodings and VTM anchor sequences with multiple runtime variants. The evaluation addressed both compression capability and encoding runtime, as well as low-latency and error-resilience features. All technologies were derived from VTM, ECM, or NNVC frameworks, featuring modified encoder configurations and coding tools rather than entirely new architectures.

Key Findings

• In the compression capability test, 76 out of 120 test cases showed at least one submission with a non-overlapping confidence interval compared to the VTM anchor. Several methods outperformed ECM16 in visual quality and achieved notable compression gains at lower complexity. Neural-network-based approaches demonstrated clear perceptual improvements, particularly for 8K HDR content, while gains were smaller for gaming scenarios.
• In the encoding runtime test, significant improvements were observed even under strict complexity constraints: 37 of 60 test points (at both 1× and 0.2× runtime) showed statistically significant benefits over VTM. Some submissions achieved faster encoding than VTM, with only a 35% increase in decoder runtime.

Research Relevance and Outlook

The CfE results illustrate a maturing convergence between model-based and data-driven video coding, raising research questions highly relevant for the ACM SIGMM community:

• How can learned prediction and filtering networks be integrated into standard codecs while preserving interoperability and runtime control?
• What methodologies can best evaluate perceptual quality beyond PSNR, especially for HDR and immersive content?
• How can complexity-quality trade-offs be optimized for diverse hardware and latency requirements?

Building on these outcomes, JVET is preparing a Call for Proposals (CfP) for the next-generation video coding standard, with a draft planned for early 2026 and evaluation through 2027. Upcoming activities include refining test material, adding Reference Picture Resampling (RPR), and forming a new ad hoc group on hardware implementation complexity.

For multimedia researchers, this CfE marks a pivotal step toward AI-assisted, complexity-adaptive, and perceptually optimized compression systems, which are considered a key frontier where codec standardization meets intelligent multimedia research.

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The 153rd MPEG meeting will be held online from January 19 to January 23, 2026. Click here for more information about MPEG meetings and their developments.

Happy World Standards Day 2025!

Celebrating innovation, interoperability, and collaboration through international standards.

Every year on October 14, we celebrate World Standards Day — honoring the collective efforts of experts and organizations worldwide who develop and maintain the standards that make modern digital life possible. For the Moving Picture Experts Group (MPEG), this day marks decades of work in defining the technologies that power media, streaming, and immersive experiences worldwide.

A Year of Progress and New Milestones

Over the past year, MPEG and its working groups achieved remarkable progress across video, audio, systems, and AI-driven technologies — advancing the future of multimedia communication. Hot off the press, MPEG is proud to announce another Emmy® Technology & Engineering Award — this time for the Common Media Application Format (CMAF; ISO/IEC 23000-19), a landmark standard that brought long-awaited harmonization between DASH and HLS streaming formats (among others).

Next Generation Video Coding Beyond VVC

The Joint Video Experts Team (JVET), a joint effort of ISO/IEC and ITU-T, launched a Call for Evidence exploring technologies that go beyond Versatile Video Coding (VVC).

The goal: to identify breakthroughs that significantly improve compression efficiency, runtime performance, and functionality — from HDR and 8K video to gaming and user-generated content. Depending on the results, a Call for Proposals (CfP) for the next generation of video coding may follow in 2026, opening the door to AI-enhanced compression.

The current plan foresees a draft CfP in January 2026, followed by the final CfP in July 2026 and submissions in November 2026, with evaluations scheduled for January 2027. The first version of the resulting standard is expected to be finalized within three years thereafter.

MPEG-DASH (Sixth Edition)

Adaptive streaming continues to evolve, and the sixth edition of MPEG-DASH (ISO/IEC 23009-1) marks a major step forward. New features include enhanced low-latency streaming, content steering across multiple CDNs, compact signaling for faster playback, and even support for interactive storylines — enabling richer, more dynamic media experiences. MPEG-DASH remains the foundation of scalable, interoperable video streaming used by billions of devices worldwide.

AI and Machine-Oriented Coding

MPEG’s vision for Audio and Video Coding for Machines continues to take shape. The updated Call for Proposals on Audio Coding for Machines (ACoM) invites technologies for efficiently compressing audio and multi-dimensional signals — not only for human listening but also for machine learning and AI-driven analysis. In parallel, Video Coding for Machines (VCM) is being standardized to optimize visual data for computer vision and autonomous systems, reducing bitrate while preserving task-relevant features.

Open Font Format (Fifth Edition)

MPEG Systems (WG 3) reached the Final Draft International Standard (FDIS) stage for the fifth edition of the Open Font Format (ISO/IEC 14496-22). This major update removes previous technical constraints, supporting over 64K glyphs and the entire Unicode range in a single file — a leap toward more inclusive digital typography across languages and writing systems.

3D and Volumetric Media Innovation

From Video-Based Dynamic Mesh Coding (V-DMC) to Low Latency Point Cloud Compression (L3C2), MPEG advanced two pivotal 3D graphics standards to final draft status. These technologies support real-time 3D content — from immersive AR/VR experiences to LiDAR-based perception in autonomous vehicles — enabling efficient, low-latency, and interoperable volumetric media.

Ensuring Media Authenticity

New amendments to MPEG Audio standards introduce mechanisms for Media Authenticity, allowing verification of content integrity and provenance across audio, video, and system layers. This step is essential for a trustworthy digital media ecosystem.

Genomics and AI Meet Multimedia

MPEG also looked beyond traditional media: the MPEG-G Genomics Hackathon, co-organized with partners such as Stanford Medicine, Philips, and Fudan University, challenges researchers to apply AI to microbiome data encoded in MPEG-G format. The goal: uncover new biomedical insights through standard-based, interoperable data compression.

Looking Ahead

From next-generation video compression and AI-enhanced codecs to trustworthy media and adaptive streaming, MPEG continues to define the building blocks of interoperable multimedia. As new technologies reshape how we experience and analyze content, standards ensure that innovation remains open, efficient, and globally accessible.

On this World Standards Day, we celebrate the dedication of all MPEG experts and contributors for shaping a smarter, more connected multimedia future.

Learn more at www.mpeg.org and stay tuned for updates from the next MPEG meeting in early 2026.

Full Professor of Virtual and Augmented Reality (all genders welcome)

The official and legally binding job description is available here.

The University of Klagenfurt wants to attract more qualified women for professorships.

The University of Klagenfurt is pleased to announce the following open position in the Department of Information Technology (ITEC) within the Faculty of Technical Sciences, in compliance with the provisions of Art. 98 (open-ended) or Art. 99 (limited to 5 years) of the Austrian Universities Act:

Full Professor of Virtual and Augmented Reality (all genders welcome)

This is a full-time position. Whether the position will be implemented in compliance with the provisions of Art. 98 Austrian Universities Act (open-ended) or Art. 99 of the Austrian Universities Act (limited to 5 years) will be decided in the course of the appointment procedure.

The University of Klagenfurt is a young, vibrant, and innovative university, located at the intersection of Alpine and Mediterranean culture in an area that offers an exceptionally high quality of life. As a public university pursuant to Art. 6 of the Austrian Universities Act, it receives federal funding. The Times Higher Education (THE) Young University Rankings 2021 ranked it among the 50 best young universities in the world. The university operates under the motto “Beyond Boundaries!”.

In accordance with its key strategic road map, the development plan, the university’s primary guiding principles and objectives include the pursuit of scientific excellence regarding the appointment of professors, favourable research conditions, a good faculty-student ratio, and the promotion of the development of young scientists.

The professorship will be embedded in the Department of Information Technology (ITEC; https://itec.aau.at/) within the Faculty of Technical Sciences (https://www.aau.at/en/tewi), which focuses on distributed multimedia systems, including multimedia coding, transmission, and quality of experience, AI-based multimedia analysis, game studies and engineering, as well as distributed cloud and edge computing. The department and faculty provide a vivid, friendly, and research-oriented environment. We are looking for a highly qualified and internationally recognized scientist with high engagement in developing and sustaining an ambitious and innovative research programme.

Virtual and Augmented Reality (VR/AR) are broad research fields addressing both theoretical and application-driven questions. This position offers an opportunity to focus on cutting-edge VR/AR research areas including – but not limited to – immersive media (e.g., 360° videos, 3D point clouds), AI for object recognition in VR/AR (e.g., in industry and medicine), educational and training applications, computer graphics, sensor technology, human-computer interaction, and efficient multimedia data transmission and cloud/edge processing.

The professor will be involved in teaching in a variety of degree programmes, including the Bachelor’s programmes “Applied Informatics” and “Robotics and Artificial Intelligence”, and the international Master’s programmes “Informatics” and “Game Studies and Engineering”.

The duties of the position include:

• Representing the field of Virtual and Augmented Reality in research and teaching
• Acquiring and managing competitive research funding
• Collaborating with colleagues across the university and with industry partners
• Teaching in relevant Bachelor’s, Master’s, and Doctoral programmes
• Advising and mentoring students and early career researchers
• Contributing to the long-term development of the department and its international standing
• Advancing the department’s and faculty’s research priorities, with a commitment to interdisciplinary collaboration
• Contributing to university governance and academic self-administration
• Engaging in third mission activities and public outreach

Required qualifications:

• Habilitation or equivalent qualification in a relevant field
• Excellent research standing and publication record in Virtual and/or Augmented Reality, including theoretical and technical foundations
• Experience in the acquisition of competitive third-party funded research projects of a relevant volume
• Teaching experience at university level and didactic competence
• Experience in the (co-)supervision of academic theses
• Collaboration and social skills
• Fluency in English

Desired qualifications:

• Excellent scientific communication and dissemination skills
• Interdisciplinary experience
• Experience with academic management duties
• Competence in leadership and management of teams
• Competence in gender mainstreaming and diversity management
• Fluency in German

German language skills are not a formal prerequisite, but proficiency at level B2 is expected within two years. The remit of the professorship requires that the successful candidate will establish Klagenfurt as primary place of work.

The university is committed to increasing the number of women among the faculty, particularly in high-level positions, and therefore specifically invites applications from qualified women. Among equally qualified candidates, women will receive preferential consideration. People with disabilities or chronic diseases who meet the qualification criteria are explicitly invited to apply.

The salary is subject to negotiation. The minimum gross salary for the position at this level (salary group A1 for faculty according to the Austrian Universities’ Collective Bargaining Agreement) is currently € 92,500 per year.

In accordance with the Austrian Income Tax Act an attractive relocation tax allowance can be granted for the first five years in the case of appointments to professorships in Austria. The prerequisites are subject to examination on a case-by-case basis.

Please submit your application in English by e-mail to the University of Klagenfurt, Office of the Senate, attn. Mag.a (FH) Sabine Seebacher via application_professorship@aau.at no later than September 28, 2025, including:

• a mandatory principal part not exceeding five pages https://jobs.aau.at/wp-content/uploads/specimen_main_part_application_professorship.doc). The submission of the mandatory principal part mentioned above constitutes a necessary condition for the validity of your application.
• one single PDF including:
• a letter of motivation
• a detailed scientific CV
• a comprehensive list of publications, talks, and courses taught
• a list of acquired third-party funded research projects, including role, funding organization, and amount of funding (in case of funding acquired within a consortium, please specify the amount attributed to you)
• a compact research statement of up to two pages
• supplementary documents, where applicable (e.g., course evaluations)
• links to publicly available versions of your three most important publications within the scope of this professorship

For general information, please refer to the general information on our website provided at https://jobs.aau.at/en/the-university-as-employer/. For specific information about the position, please contact Prof. Dr. Christian Timmerer (christian.timmerer@aau.at).