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HNeRV: A Hybrid Neural Representation for Videos

CVPR 2023 · Video › Video segmentation and tracking · approach: Neural video representations · 118 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use learnable content-adaptive frame embeddings and the HNeRV decoderVideo regression · Bunny, 0.75M parameters, 300 epochsPSNR: 28.46 -> 32.81Helped
Use learnable content-adaptive frame embeddings and the HNeRV decoderVideo regression · UVG and DAVIS, 960×1920PSNR: 29.94 -> 31.49Helped
Use learnable content-adaptive embeddingsHNeRV · UVG held-out-frame internal generalizationPSNR: 22.82 -> 26.15Helped
Use HNeRV for video inpaintingHNeRV · UVG, 5 fixed box masksPSNR: 31.14 -> 32.03Helped
Use HNeRV instead of IIVIVideo inpainting · UVG, 5 fixed box masksPSNR: 32.97 -> 32.03Hurt
Use the HNeRV decoder instead of H.264Bunny decoding at PSNR 35 · BunnyFPS: 240.9 -> 332.7Helped
Use HNeRV with larger later-layer kernels and wider channels (ablation)HNeRV · Bunny regression, parameter distributionPSNR: 29.91 -> 35.57Helped
Set Kmax to 3 instead of 5 (ablation)HNeRV · Bunny kernel-size ablationPSNR: 35.57 -> 35.02Hurt
Set Kmax to 7 instead of 5 (ablation)HNeRV · Bunny kernel-size ablationPSNR: 35.57 -> 35.07Hurt
Set channel reduction r to 1 instead of 1.2 (ablation)HNeRV · Bunny channel-reduction ablationPSNR: 35.57 -> 34.96Hurt
Set channel reduction r to 1.5 instead of 1.2 (ablation)HNeRV · Bunny channel-reduction ablationPSNR: 35.57 -> 34.98Hurt
Set channel reduction r to 2 instead of 1.2 (ablation)HNeRV · Bunny channel-reduction ablationPSNR: 35.57 -> 34.32Hurt

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