Low-complexity Deep Video Compression with A Distributed Coding Architecture
This project introduces a deep video compression framework with a distributed coding architecture, aiming to reduce encoding complexity while maintaining competitive performance. It offers significant encoding speed improvements, making it suitable for deployment on resource-cons
Link
Related resources
- MLVC: Multi-platform Learned Video Codec for Real-World DeploymentAcademic paper on a neural video codec targeting competitive compression, real-time speed, and cross-platform (Apple/Intel/Qualcomm NPU) in…
- CompressAI-Vision: Video Compression for Machines BenchmarkPaper + framework for designing, testing and comparing "video coding for machines" pipelines, mixing neural CompressAI models against VVC/H…
- av1-codec-comparisonGoogle internship research project comparing SVT-AV1 and rav1e coding tools against libaom for quality and speed.
- Performance Comparison of AV1, JEM, VP9, and HEVC EncodersFraunhofer HHI SPIE 2017 paper comparing codec internals, BD-BR, and complexity across AV1, JEM, VP9, and HEVC.
- DeepGameReal-time content-adaptive encoding for cloud gaming using spatiotemporal DNN to weight regions by player gaze/interest, cutting bandwidth…
- Opus (xiph/opus)Reference implementation of the Opus audio codec, recently adding deep-learning-based packet loss concealment.
- FOSDEM 2024: VVdeC<>Arm — Optimizing an Open Source VVC Decoder for Arm ArchitecturesFOSDEM Open Media devroom talk detailing Arm-specific performance optimization work on the open-source VVdeC VVC decoder.
- Differentiable VMAF Re-implementation on PyTorchDifferentiable PyTorch reimplementation of VMAF metric enabling gradient-based codec/RDO optimization, with companion code.
- nano-hevcMinimal educational HEVC encoder written in pure Python, readable-over-fast, for teaching codec internals.
- dav1d.wasmWASM port of the dav1d AV1 decoder, SIMD-optimized with TypeScript interfaces, aimed at production use in browsers.