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M-LVC: Multiple Frames Prediction for Learned Video Compression

CVPR 2020 · Video › Video segmentation and tracking · approach: Learned video compression · 216 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add MAMVP-Net to predict motion vectors from multiple prior MV fields (ablation)Our Baseline · HEVC Class DPSNR: about 0.5~0.7 dBHelped
Add MV refinement after MAMVP-Net (ablation)Add MAMVP-Net · HEVC Class DPSNR: about 0.15dB at high bit rates and about 0.4dB at low bit ratesHelped
Add the previous reconstructed frame as an MV Refine-Net input (ablation)Add MVRefine-Net-0 · HEVC Class DPSNR: about 0.1dBHelped
Use multiple reference frames in motion compensation (ablation)Add MVRefine-Net · HEVC Class DPSNR: about 0.1~0.25dBHelped
Add residual refinement (ablation)Add MMC-Net · HEVC Class DPSNR: about 0.3dB gain at low bit rates and about 0.2dB gain at high bit ratesHelped
Train the proposed network from scratch instead of using step-by-step training (ablation)Proposed · Kimonobitrate allocation: 0.0002bpp for MVD and 0.2431bpp for residualHurt
Use multi-scale aligned MV prediction rather than single-scale w/o alignment (ablation)MAMVP-Net · HEVC Class DPSNR (dB): 31.250 -> 31.290Helped
Use multi-scale aligned MV prediction rather than single-scale w/o alignment (ablation)MAMVP-Net · HEVC Class Dbpp: 0.297 -> 0.285Helped
Replace single-reference motion compensation with multiple-reference MMC-Net (ablation)Add MVRefine-Net · BasketballPass, frame 9PSNR of predicted frame: 31.42dB -> 31.97dBHelped
Increase the number of reference frames from two to three or four (ablation)M-LVC · HEVC Class Dcompression efficiencyHelped

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