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MuCAN: Multi-Correspondence Aggregation Network for Video Super-Resolution

arXiv 2007.11803 ↗First posted 23 Jul 2020cs.CVcited by 89

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Abstract (arXiv)

Video super-resolution (VSR) aims to utilize multiple low-resolution frames to generate a high-resolution prediction for each frame. In this process, inter- and intra-frames are the key sources for exploiting temporal and spatial information. However, there are a couple of limitations for existing VSR methods. First, optical flow is often used to establish temporal correspondence. But flow estimation itself is error-prone and affects recovery results. Second, similar patterns existing in natural images are rarely exploited for the VSR task. Motivated by these findings, we propose a temporal multi-correspondence aggregation strategy to leverage similar patches across frames, and a cross-scale nonlocal-correspondence aggregation scheme to explore self-similarity of images across scales. Based on these two new modules, we build an effective multi-correspondence aggregation network (MuCAN) for VSR. Our method achieves state-of-the-art results on multiple benchmark datasets. Extensive experiments justify the effectiveness of our method.

Key facts. Cited by 89 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Jul 2020.

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Citing papers per year: 2021: 15; 2022: 25; 2023: 12; 2024: 9; 2025: 24; 2026: 4.

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  1. 2021BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignmentcited by 340
  2. 2022VRT: A Video Restoration Transformercited by 219
  3. 2022Recurrent Video Restoration Transformer with Guided Deformable Attentioncited by 168
  4. 2022Rethinking Alignment in Video Super-Resolution Transformerscited by 71
  5. 2022Learning Trajectory-Aware Transformer for Video Super-Resolutioncited by 61
  6. 2023Motion-Guided Latent Diffusion for Temporally Consistent Real-world Video Super-resolutioncited by 59
  7. 2025STAR: Spatial-Temporal Augmentation with Text-to-Video Models for Real-World Video Super-Resolutioncited by 56
  8. 2021AdaPool: Exponential Adaptive Pooling for Information-Retaining Downsamplingcited by 47
  9. 2025FlashVSR: Towards Real-Time Diffusion-Based Streaming Video Super-Resolutioncited by 40
  10. 2023Enhancing Video Super-Resolution via Implicit Resampling-based Alignmentcited by 35
  11. 2024DiffIR2VR-Zero: Zero-Shot Video Restoration with Diffusion-based Image Restoration Modelscited by 33
  12. 2021Best-Buddy GANs for Highly Detailed Image Super-Resolutioncited by 30
38 more
  1. 2024VideoGigaGAN: Towards Detail-rich Video Super-Resolutioncited by 30
  2. 2025DOVE: Efficient One-Step Diffusion Model for Real-World Video Super-Resolutioncited by 30
  3. 2022Mitigating Artifacts in Real-World Video Super-Resolution Modelscited by 29
  4. 2024Video Super-Resolution Transformer with Masked Inter&Intra-Frame Attentioncited by 29
  5. 2024FMA-Net: Flow-Guided Dynamic Filtering and Iterative Feature Refinement with Multi-Attention for Joint Video Super-Resolution and Deblurringcited by 28
  6. 2021SRWarp: Generalized Image Super-Resolution under Arbitrary Transformationcited by 26
  7. 2021COMISR: Compression-Informed Video Super-Resolutioncited by 26
  8. 2022Learning Spatiotemporal Frequency-Transformer for Compressed Video Super-Resolutioncited by 25
  9. 2021Revisiting Temporal Alignment for Video Restorationcited by 24
  10. 2022AnimeSR: Learning Real-World Super-Resolution Models for Animation Videoscited by 23
  11. 2024Learning Spatial Adaptation and Temporal Coherence in Diffusion Models for Video Super-Resolutioncited by 23
  12. 2021Lucas-Kanade Reloaded: End-to-End Super-Resolution from Raw Image Burstscited by 21
  13. 2022Look Back and Forth: Video Super-Resolution with Explicit Temporal Difference Modelingcited by 20
  14. 2021FDAN: Flow-guided Deformable Alignment Network for Video Super-Resolutioncited by 19
  15. 2022Reference-based Video Super-Resolution Using Multi-Camera Video Tripletscited by 19
  16. 2023Enhancing Perceptual Quality in Video Super-Resolution through Temporally-Consistent Detail Synthesis using Diffusion Modelscited by 18
  17. 2022Exploring Motion Ambiguity and Alignment for High-Quality Video Frame Interpolationcited by 17
  18. 2025PMQ-VE: Progressive Multi-Frame Quantization for Video Enhancementcited by 17
  19. 2022Temporal Consistency Learning of inter-frames for Video Super-Resolutioncited by 16
  20. 2021NTIRE 2021 Challenge on Video Super-Resolutioncited by 15
  21. 2025One-Step Diffusion for Detail-Rich and Temporally Consistent Video Super-Resolutioncited by 14
  22. 2024Learning Truncated Causal History Model for Video Restorationcited by 13
  23. 2022Spatial-Temporal Space Hand-in-Hand: Spatial-Temporal Video Super-Resolution via Cycle-Projected Mutual Learningcited by 12
  24. 2022Online Video Super-Resolution with Convolutional Kernel Bypass Graftcited by 12
  25. 2022Unsupervised Flow-Aligned Sequence-to-Sequence Learning for Video Restorationcited by 11
  26. 2022A Differentiable Two-stage Alignment Scheme for Burst Image Reconstruction with Large Shiftcited by 10
  27. 2021Optical Flow Reusing for High-Efficiency Space-Time Video Super Resolutioncited by 8
  28. 2022Reference-based Image and Video Super-Resolution via C2-Matchingcited by 8
  29. 2023TMP: Temporal Motion Propagation for Online Video Super-Resolutioncited by 8
  30. 2022Progressive Training of A Two-Stage Framework for Video Restorationcited by 7
  31. 2025Stream-DiffVSR: Low-Latency Streamable Video Super-Resolution via Auto-Regressive Diffusioncited by 7
  32. 2021Video Rescaling Networks with Joint Optimization Strategies for Downscaling and Upscalingcited by 6
  33. 2022STDAN: Deformable Attention Network for Space-Time Video Super-Resolutioncited by 6
  34. 2022A Codec Information Assisted Framework for Efficient Compressed Video Super-Resolutioncited by 6
  35. 2023FPANet: Frequency-based Video Demoireing using Frame-level Post Alignmentcited by 6
  36. 2023NegVSR: Augmenting Negatives for Generalized Noise Modeling in Real-World Video Super-Resolutioncited by 6
  37. 2023From NeRFLiX to NeRFLiX++: A General NeRF-Agnostic Restorer Paradigmcited by 6
  38. 2021Zooming SlowMo: An Efficient One-Stage Framework for Space-Time Video Super-Resolutioncited by 5

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