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Video Super Resolution On Vid4 4X Upscaling

Metrics

PSNR
SSIM

Results

Performance results of various models on this benchmark

Paper Title
EvTexture+29.780.8983EvTexture: Event-driven Texture Enhancement for Video Super-Resolution
EvTexture29.510.8909EvTexture: Event-driven Texture Enhancement for Video Super-Resolution
IART28.260.8517Enhancing Video Super-Resolution via Implicit Resampling-based Alignment
MIA-VSR28.200.8507Video Super-Resolution Transformer with Masked Inter&Intra-Frame Attention
CFD-PSRT28.180.8503Collaborative Feedback Discriminative Propagation for Video Super-Resolution
PSRT-recurrent28.070.8485Rethinking Alignment in Video Super-Resolution Transformers
RVRT27.990.8462Recurrent Video Restoration Transformer with Guided Deformable Attention
VRT27.930.8425VRT: A Video Restoration Transformer
BasicVSR++27.790.8400BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment
SATeCo27.440.8420Learning Spatial Adaptation and Temporal Coherence in Diffusion Models for Video Super-Resolution
IconVSR27.390.8279BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond
EDVR27.350.8264EDVR: Video Restoration with Enhanced Deformable Convolutional Networks
VSR-DUF27.330.8319Deep Video Super-Resolution Network Using Dynamic Upsampling Filters Without Explicit Motion Compensation
BasicVSR27.240.8251BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond
RBPN/6-PF27.120.8180Recurrent Back-Projection Network for Video Super-Resolution
VideoGigaGAN27.04-VideoGigaGAN: Towards Detail-rich Video Super-Resolution
SOF-VSR26.010.771Learning for Video Super-Resolution through HR Optical Flow Estimation
SOF-VSR260.772Deep Video Super-Resolution using HR Optical Flow Estimation
TecoGAN⊖25.89-Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation
DRDVSR25.880.774Detail-revealing Deep Video Super-resolution
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