Evaluating Video Quality Metrics for Neural and Traditional Codecs (4K/UHD-1)
Academic comparison of VMAF, AVQBits, and FasterVQA no-reference quality metrics on 4K content.
Link
Related resources
- Encoder-Quantization-Motion (EQM) Video Quality MetricAcademic paper on an encoder-side video quality metric for low-latency use, addressing gaps in VMAF/P.1204.3 via contrast/motion masking an…
- CompressedVQA: Full/No-Reference VQA for Compressed UGC VideoICME 2021 grand challenge-winning full-reference and no-reference video quality models for compressed user-generated content.
- GHVQ: Benchmark and Metric for AI-Generated Human-Activity Video QualityAcademic paper introducing a benchmark dataset and objective quality metric for AI-generated human-activity video, with companion code.
- VQEG Software ToolsVideo Quality Experts Group's curated index of academic/industry video quality assessment software tools and research collaboration hub.
- 2BiVQA: Double Bi-LSTM No-Reference Video Quality AssessmentNo-reference VQA model for UGC video using double Bi-LSTM, companion code to arXiv:2208.14774.
- nr-vqa-consumervideoNo-reference video quality metric tuned for consumer video capture artifacts (sensor noise, motion blur, shake) rather than compression art…
- VMAF-torchPyTorch reimplementation of VMAF metric, GPU/gradient-friendly for use in learned codec optimization loops.
- aws-batch-with-FFmpegReference architecture running FFmpeg containers (ARM64/x86-64/NVIDIA/Xilinx) on AWS Batch with Spot compute environments and SDK/REST job…
- Bitrate Ladder Construction via Transfer Learning and Spatio-Temporal FeaturesML-based bitrate ladder optimization achieving 94.1% complexity reduction at only 1.71% BD-rate cost using transfer learning.