mlsanityData to 7 Oct 2026

BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond

arXiv 2012.02181 ↗First posted 3 Dec 2020cs.CVcited by 303

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Cited by 49 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Video super-resolution (VSR) approaches tend to have more components than the image counterparts as they need to exploit the additional temporal dimension. Complex designs are not uncommon. In this study, we wish to untangle the knots and reconsider some most essential components for VSR guided by four basic functionalities, i.e., Propagation, Alignment, Aggregation, and Upsampling. By reusing some existing components added with minimal redesigns, we show a succinct pipeline, BasicVSR, that achieves appealing improvements in terms of speed and restoration quality in comparison to many state-of-the-art algorithms. We conduct systematic analysis to explain how such gain can be obtained and discuss the pitfalls. We further show the extensibility of BasicVSR by presenting an information-refill mechanism and a coupled propagation scheme to facilitate information aggregation. The BasicVSR and its extension, IconVSR, can serve as strong baselines for future VSR approaches.

Key facts. Cited by 303 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Dec 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 19; 2022: 72; 2023: 51; 2024: 48; 2025: 69; 2026: 44.

303 papers.

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  1. 2021BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignmentcited by 340
  2. 2022Exploring Video Quality Assessment on User Generated Contents from Aesthetic and Technical Perspectivescited by 314
  3. 2022FlowFormer: A Transformer Architecture for Optical Flowcited by 273
  4. 2022VRT: A Video Restoration Transformercited by 219
  5. 2023ProPainter: Improving Propagation and Transformer for Video Inpaintingcited by 193
  6. 2022VFHQ: A High-Quality Dataset and Benchmark for Video Face Super-Resolutioncited by 174
  7. 2022Recurrent Video Restoration Transformer with Guided Deformable Attentioncited by 168
  8. 2021Low-Light Image and Video Enhancement Using Deep Learning: A Surveycited by 148
  9. 2021Investigating Tradeoffs in Real-World Video Super-Resolutioncited by 133
  10. 2023Upscale-A-Video: Temporal-Consistent Diffusion Model for Real-World Video Super-Resolutioncited by 131
  11. 2022Hybrid Spatial-Temporal Entropy Modelling for Neural Video Compressioncited by 123
  12. 2021Video Super-Resolution Transformercited by 120
38 more
  1. 2024Neural Video Compression with Feature Modulationcited by 115
  2. 2023FlowFormer++: Masked Cost Volume Autoencoding for Pretraining Optical Flow Estimationcited by 114
  3. 2022Towards An End-to-End Framework for Flow-Guided Video Inpaintingcited by 111
  4. 2022IFRNet: Intermediate Feature Refine Network for Efficient Frame Interpolationcited by 107
  5. 2022VideoINR: Learning Video Implicit Neural Representation for Continuous Space-Time Super-Resolutioncited by 101
  6. 2023VideoFlow: Exploiting Temporal Cues for Multi-frame Optical Flow Estimationcited by 82
  7. 2022Rethinking Alignment in Video Super-Resolution Transformerscited by 71
  8. 2022A Simple Baseline for Video Restoration with Grouped Spatial-temporal Shiftcited by 68
  9. 2024VEnhancer: Generative Space-Time Enhancement for Video Generationcited by 64
  10. 2025SeedVR: Seeding Infinity in Diffusion Transformer Towards Generic Video Restorationcited by 62
  11. 2022Learning Trajectory-Aware Transformer for Video Super-Resolutioncited by 61
  12. 2023Motion-Guided Latent Diffusion for Temporally Consistent Real-world Video Super-resolutioncited by 59
  13. 2025STAR: Spatial-Temporal Augmentation with Text-to-Video Models for Real-World Video Super-Resolutioncited by 56
  14. 2023Towards Explainable In-the-Wild Video Quality Assessment: A Database and a Language-Prompted Approachcited by 45
  15. 2025SeedVR2: One-Step Video Restoration via Diffusion Adversarial Post-Trainingcited by 45
  16. 2023DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution Modelscited by 41
  17. 2025FlashVSR: Towards Real-Time Diffusion-Based Streaming Video Super-Resolutioncited by 40
  18. 2023Enhancing Video Super-Resolution via Implicit Resampling-based Alignmentcited by 35
  19. 2023Learning Spatial-Temporal Implicit Neural Representations for Event-Guided Video Super-Resolutioncited by 33
  20. 2024DiffIR2VR-Zero: Zero-Shot Video Restoration with Diffusion-based Image Restoration Modelscited by 33
  21. 2024RealViformer: Investigating Attention for Real-World Video Super-Resolutioncited by 33
  22. 2022Bringing Old Films Back to Lifecited by 31
  23. 2021Omniscient Video Super-Resolutioncited by 30
  24. 2024VideoGigaGAN: Towards Detail-rich Video Super-Resolutioncited by 30
  25. 2025DOVE: Efficient One-Step Diffusion Model for Real-World Video Super-Resolutioncited by 30
  26. 2022Mitigating Artifacts in Real-World Video Super-Resolution Modelscited by 29
  27. 2023NeRFLiX: High-Quality Neural View Synthesis by Learning a Degradation-Driven Inter-viewpoint MiXercited by 29
  28. 2024Video Super-Resolution Transformer with Masked Inter&Intra-Frame Attentioncited by 29
  29. 2024FMA-Net: Flow-Guided Dynamic Filtering and Iterative Feature Refinement with Multi-Attention for Joint Video Super-Resolution and Deblurringcited by 28
  30. 2022Fast and Memory-Efficient Network Towards Efficient Image Super-Resolutioncited by 27
  31. 2021NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Resultscited by 26
  32. 2023OSRT: Omnidirectional Image Super-Resolution with Distortion-aware Transformercited by 26
  33. 2021Deep Recurrent Neural Network with Multi-scale Bi-directional Propagation for Video Deblurringcited by 25
  34. 2022Learning Spatiotemporal Frequency-Transformer for Compressed Video Super-Resolutioncited by 25
  35. 2021Revisiting Temporal Alignment for Video Restorationcited by 24
  36. 2022Video Demoireing with Relation-Based Temporal Consistencycited by 24
  37. 2022Unidirectional Video Denoising by Mimicking Backward Recurrent Modules with Look-ahead Forward Onescited by 24
  38. 2025MatAnyone: Stable Video Matting with Consistent Memory Propagationcited by 24

50 most cited of 303 All 303 (JSON)