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Video Super-resolution with Temporal Group Attention

arXiv 2007.10595 ↗First posted 21 Jul 2020cs.CVcited by 81

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Abstract (arXiv)

Video super-resolution, which aims at producing a high-resolution video from its corresponding low-resolution version, has recently drawn increasing attention. In this work, we propose a novel method that can effectively incorporate temporal information in a hierarchical way. The input sequence is divided into several groups, with each one corresponding to a kind of frame rate. These groups provide complementary information to recover missing details in the reference frame, which is further integrated with an attention module and a deep intra-group fusion module. In addition, a fast spatial alignment is proposed to handle videos with large motion. Extensive results demonstrate the capability of the proposed model in handling videos with various motion. It achieves favorable performance against state-of-the-art methods on several benchmark datasets.

Key facts. Cited by 81 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Jul 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 21; 2022: 24; 2023: 15; 2024: 8; 2025: 11; 2026: 2.

81 papers.

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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. 2021PSCC-Net: Progressive Spatio-Channel Correlation Network for Image Manipulation Detection and Localizationcited by 133
  5. 2021Investigating Tradeoffs in Real-World Video Super-Resolutioncited by 133
  6. 2023Upscale-A-Video: Temporal-Consistent Diffusion Model for Real-World Video Super-Resolutioncited by 131
  7. 2021Video Super-Resolution Transformercited by 120
  8. 2024VEnhancer: Generative Space-Time Enhancement for Video Generationcited by 64
  9. 2022Learning Trajectory-Aware Transformer for Video Super-Resolutioncited by 61
  10. 2022TAPE: Task-Agnostic Prior Embedding for Image Restorationcited by 54
  11. 2021Multi-Target Domain Adaptation with Collaborative Consistency Learningcited by 43
  12. 2022Low-Light Video Enhancement with Synthetic Event Guidancecited by 33
38 more
  1. 2023Learning Spatial-Temporal Implicit Neural Representations for Event-Guided Video Super-Resolutioncited by 33
  2. 2021Omniscient 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. 2024Learning Spatial Adaptation and Temporal Coherence in Diffusion Models for Video Super-Resolutioncited by 23
  7. 2022Look Back and Forth: Video Super-Resolution with Explicit Temporal Difference Modelingcited by 20
  8. 2021FDAN: Flow-guided Deformable Alignment Network for Video Super-Resolutioncited by 19
  9. 2021Self-Conditioned Probabilistic Learning of Video Rescalingcited by 19
  10. 2023Local-Global Temporal Difference Learning for Satellite Video Super-Resolutioncited by 19
  11. 2021Learning for Unconstrained Space-Time Video Super-Resolutioncited by 18
  12. 2021Memory-Augmented Non-Local Attention for Video Super-Resolutioncited by 17
  13. 2022Temporal Consistency Learning of inter-frames for Video Super-Resolutioncited by 16
  14. 2021NTIRE 2021 Challenge on Video Super-Resolutioncited by 15
  15. 2022Self-Supervised Deep Blind Video Super-Resolutioncited by 15
  16. 2022Structured Sparsity Learning for Efficient Video Super-Resolutioncited by 14
  17. 2024Learning Truncated Causal History Model for Video Restorationcited by 13
  18. 2025Show and Polish: Reference-Guided Identity Preservation in Face Video Restorationcited by 12
  19. 2022A Differentiable Two-stage Alignment Scheme for Burst Image Reconstruction with Large Shiftcited by 10
  20. 2021Triple-level Model Inferred Collaborative Network Architecture for Video Derainingcited by 9
  21. 2022Deep Parametric 3D Filters for Joint Video Denoising and Illumination Enhancement in Video Super Resolutioncited by 9
  22. 2021Optical Flow Reusing for High-Efficiency Space-Time Video Super Resolutioncited by 8
  23. 2022Local Motion and Contrast Priors Driven Deep Network for Infrared Small Target Super-Resolutioncited by 8
  24. 2022Reference-based Image and Video Super-Resolution via C2-Matchingcited by 8
  25. 2023Scale-Adaptive Feature Aggregation for Efficient Space-Time Video Super-Resolutioncited by 8
  26. 2023TMP: Temporal Motion Propagation for Online Video Super-Resolutioncited by 8
  27. 2021SiamTrans: Zero-Shot Multi-Frame Image Restoration with Pre-Trained Siamese Transformerscited by 7
  28. 2021Video Rescaling Networks with Joint Optimization Strategies for Downscaling and Upscalingcited by 6
  29. 2021Stable Long-Term Recurrent Video Super-Resolutioncited by 6
  30. 2022STDAN: Deformable Attention Network for Space-Time Video Super-Resolutioncited by 6
  31. 2024Deep Blind Super-Resolution for Satellite Videocited by 6
  32. 2024HR-INR: Continuous Space-Time Video Super-Resolution via Event Cameracited by 6
  33. 2025A Survey on fMRI-based Brain Decoding for Reconstructing Multimodal Stimulicited by 6
  34. 2022Towards True Detail Restoration for Super-Resolution: A Benchmark and a Quality Metriccited by 5
  35. 2025Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolutioncited by 5
  36. 2025A Survey of Deep Learning Video Super-Resolutioncited by 5
  37. 2026SparkVSR: Interactive Video Super-Resolution via Sparse Keyframe Propagationcited by 5
  38. 2022Optical Flow for Video Super-Resolution: A Surveycited by 4

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