Research map / Video / Video segmentation and tracking
M-LVC: Multiple Frames Prediction for Learned Video Compression
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add MAMVP-Net to predict motion vectors from multiple prior MV fields (ablation) | Our Baseline · HEVC Class D | PSNR: about 0.5~0.7 dB | Helped |
| Add MV refinement after MAMVP-Net (ablation) | Add MAMVP-Net · HEVC Class D | PSNR: about 0.15dB at high bit rates and about 0.4dB at low bit rates | Helped |
| Add the previous reconstructed frame as an MV Refine-Net input (ablation) | Add MVRefine-Net-0 · HEVC Class D | PSNR: about 0.1dB | Helped |
| Use multiple reference frames in motion compensation (ablation) | Add MVRefine-Net · HEVC Class D | PSNR: about 0.1~0.25dB | Helped |
| Add residual refinement (ablation) | Add MMC-Net · HEVC Class D | PSNR: about 0.3dB gain at low bit rates and about 0.2dB gain at high bit rates | Helped |
| Train the proposed network from scratch instead of using step-by-step training (ablation) | Proposed · Kimono | bitrate allocation: 0.0002bpp for MVD and 0.2431bpp for residual | Hurt |
| Use multi-scale aligned MV prediction rather than single-scale w/o alignment (ablation) | MAMVP-Net · HEVC Class D | PSNR (dB): 31.250 -> 31.290 | Helped |
| Use multi-scale aligned MV prediction rather than single-scale w/o alignment (ablation) | MAMVP-Net · HEVC Class D | bpp: 0.297 -> 0.285 | Helped |
| Replace single-reference motion compensation with multiple-reference MMC-Net (ablation) | Add MVRefine-Net · BasketballPass, frame 9 | PSNR of predicted frame: 31.42dB -> 31.97dB | Helped |
| Increase the number of reference frames from two to three or four (ablation) | M-LVC · HEVC Class D | compression efficiency | Helped |
Closest papers by meaning
- ECVC: Exploiting Non-Local Correlations in Multiple Frames for Contextual Video Compression (CVPR 2025 · similarity 0.88)
- Neural Video Compression with Context Modulation (CVPR 2025 · similarity 0.86)
- FLAVC: Learned Video Compression with Feature Level Attention (CVPR 2025 · similarity 0.86)
- Neural B-frame Video Compression with Bi-directional Reference Harmonization (NeurIPS 2025 · similarity 0.85)
- Deep Hierarchical Video Compression (AAAI 2024 · similarity 0.85)
- Neural Video Compression with Feature Modulation (CVPR 2024 · similarity 0.85)
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