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Video Super Resolution On Vid4 4X Upscaling

评估指标

PSNR
SSIM

评测结果

各个模型在此基准测试上的表现结果

模型名称
PSNR
SSIM
Paper TitleRepository
MIA-VSR28.200.8507Video Super-Resolution Transformer with Masked Inter&Intra-Frame Attention
VideoGigaGAN27.04-VideoGigaGAN: Towards Detail-rich Video Super-Resolution-
IconVSR27.390.8279BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond
EvTexture+29.780.8983EvTexture: Event-driven Texture Enhancement for Video Super-Resolution
BasicVSR27.240.8251BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond
BRCN24.430.662Bidirectional Recurrent Convolutional Networks for Multi-Frame Super-Resolution-
RVRT27.990.8462Recurrent Video Restoration Transformer with Guided Deformable Attention
SATeCo27.440.8420Learning Spatial Adaptation and Temporal Coherence in Diffusion Models for Video Super-Resolution-
ESPCN25.060.7394Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network
DBPN25.370.737Deep Back-Projection Networks For Super-Resolution
DRDVSR25.880.774Detail-revealing Deep Video Super-resolution
RBPN/6-PF27.120.8180Recurrent Back-Projection Network for Video Super-Resolution
CFD-PSRT28.180.8503Collaborative Feedback Discriminative Propagation for Video Super-Resolution
IART28.260.8517Enhancing Video Super-Resolution via Implicit Resampling-based Alignment
VESPCN25.350.7557Real-Time Video Super-Resolution with Spatio-Temporal Networks and Motion Compensation-
BasicVSR++27.790.8400BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment
PSRT-recurrent28.070.8485Rethinking Alignment in Video Super-Resolution Transformers
VRT27.930.8425VRT: A Video Restoration Transformer
TecoGAN⊖25.89-Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation
SOF-VSR26.010.771Learning for Video Super-Resolution through HR Optical Flow Estimation
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