Improving Our Video Encodes for Legacy Devices
A Netflix Tech Blog post describing techniques to ensure Netflix content remains compatible and efficient on older or less powerful devices, through specialized encoding profiles and optimizations.
Link
Related resources
- DeepGameReal-time content-adaptive encoding for cloud gaming using spatiotemporal DNN to weight regions by player gaze/interest, cutting bandwidth…
- Sustainable Real-Time 8K60 HEVC Encoding for V2XPaper on repurposing legacy Pascal-generation NVENC hardware for real-time 8K60 HEVC encoding via split-frame encoding, targeting V2X appli…
- VidaptiveDecouples video encoding from transport, pacing frames at congestion-control rate and dynamically retargeting encoder bitrate to CCA capaci…
- VoltageFFmpeg-based encoding API supporting concurrent instances with a priority/retry job queue and webhook notifications.
- Evaluation of NVENC Split-Frame Encoding (SFE) for UHD Video TranscodingAcademic evaluation of NVENC's split-frame encoding feature for UHD video transcoding throughput and quality.
- Differentiable VMAF Re-implementation on PyTorchDifferentiable PyTorch reimplementation of VMAF metric enabling gradient-based codec/RDO optimization, with companion code.
- 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.
- nano-hevcMinimal educational HEVC encoder written in pure Python, readable-over-fast, for teaching codec internals.
- Opus (xiph/opus)Reference implementation of the Opus audio codec, recently adding deep-learning-based packet loss concealment.
- dav1d.wasmWASM port of the dav1d AV1 decoder, SIMD-optimized with TypeScript interfaces, aimed at production use in browsers.