mlsanityData to 14 Oct 2026

Deep Feature Flow for Video Recognition

arXiv 1611.07715 ↗First posted 23 Nov 2016cs.CVcited by 186

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Abstract (arXiv)

Deep convolutional neutral networks have achieved great success on image recognition tasks. Yet, it is non-trivial to transfer the state-of-the-art image recognition networks to videos as per-frame evaluation is too slow and unaffordable. We present deep feature flow, a fast and accurate framework for video recognition. It runs the expensive convolutional sub-network only on sparse key frames and propagates their deep feature maps to other frames via a flow field. It achieves significant speedup as flow computation is relatively fast. The end-to-end training of the whole architecture significantly boosts the recognition accuracy. Deep feature flow is flexible and general. It is validated on two recent large scale video datasets. It makes a large step towards practical video recognition.

Key facts. Cited by 186 papers in the map (data through 14 Oct 2026). First posted on arXiv 23 Nov 2016.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 49; 2022: 41; 2023: 36; 2024: 30; 2025: 12; 2026: 18.

186 papers.

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  1. 2022BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformerscited by 1,218
  2. 2021KITTI-360: A Novel Dataset and Benchmarks for Urban Scene Understanding in 2D and 3Dcited by 575
  3. 2021Occluded Video Instance Segmentation: A Benchmarkcited by 154
  4. 2021A Survey on Deep Learning Technique for Video Segmentationcited by 132
  5. 2023Transformer-Based Visual Segmentation: A Surveycited by 124
  6. 2022Video K-Net: A Simple, Strong, and Unified Baseline for Video Segmentationcited by 79
  7. 2022TransVOD: End-to-End Video Object Detection with Spatial-Temporal Transformerscited by 78
  8. 2021Adaptive Focus for Efficient Video Recognitioncited by 77
  9. 2021STEP: Segmenting and Tracking Every Pixelcited by 73
  10. 2023Semantic Segmentation using Vision Transformers: A surveycited by 73
  11. 2021Self-Supervised Monocular Depth and Ego-Motion Estimation in Endoscopy: Appearance Flow to the Rescuecited by 72
  12. 2022MPPNet: Multi-Frame Feature Intertwining with Proxy Points for 3D Temporal Object Detectioncited by 65
38 more
  1. 2021Temporal Memory Attention for Video Semantic Segmentationcited by 50
  2. 2021Temporal RoI Align for Video Object Recognitioncited by 44
  3. 2021End-to-End Video Object Detection with Spatial-Temporal Transformerscited by 40
  4. 2021TF-Blender: Temporal Feature Blender for Video Object Detectioncited by 37
  5. 2021PolyphonicFormer: Unified Query Learning for Depth-aware Video Panoptic Segmentationcited by 36
  6. 2022TubeFormer-DeepLab: Video Mask Transformercited by 35
  7. 2023Time Does Tell: Self-Supervised Time-Tuning of Dense Image Representationscited by 35
  8. 2021Deep Learning for UAV-based Object Detection and Tracking: A Surveycited by 33
  9. 2023Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentationcited by 33
  10. 2021Skip-Convolutions for Efficient Video Processingcited by 32
  11. 2022Stubborn: A Strong Baseline for Indoor Object Navigationcited by 32
  12. 2022A New Dataset and A Baseline Model for Breast Lesion Detection in Ultrasound Videoscited by 32
  13. 2021AuxAdapt: Stable and Efficient Test-Time Adaptation for Temporally Consistent Video Semantic Segmentationcited by 31
  14. 2023Flow-Based Feature Fusion for Vehicle-Infrastructure Cooperative 3D Object Detectioncited by 31
  15. 2023Discovering Sounding Objects by Audio Queries for Audio Visual Segmentationcited by 29
  16. 2024Video Super-Resolution Transformer with Masked Inter&Intra-Frame Attentioncited by 29
  17. 2021Self-Supervised Representation Learning from Flow Equivariancecited by 28
  18. 2021LiDAR-based Recurrent 3D Semantic Segmentation with Temporal Memory Alignmentcited by 26
  19. 2022PanoFlow: Learning 360deg Optical Flow for Surrounding Temporal Understandingcited by 26
  20. 2023Mask Propagation for Efficient Video Semantic Segmentationcited by 26
  21. 2021Local Memory Attention for Fast Video Semantic Segmentationcited by 25
  22. 2021Learning to Associate Every Segment for Video Panoptic Segmentationcited by 25
  23. 2022Mining Relations among Cross-Frame Affinities for Video Semantic Segmentationcited by 25
  24. 2023Vehicle-Infrastructure Cooperative 3D Object Detection via Feature Flow Predictioncited by 25
  25. 2022Learning Local and Global Temporal Contexts for Video Semantic Segmentationcited by 24
  26. 2023Video-kMaX: A Simple Unified Approach for Online and Near-Online Video Panoptic Segmentationcited by 24
  27. 2023Tube-Link: A Flexible Cross Tube Framework for Universal Video Segmentationcited by 23
  28. 2022Exploiting Temporal Relations on Radar Perception for Autonomous Drivingcited by 22
  29. 2021Domain Adaptive Video Segmentation via Temporal Consistency Regularizationcited by 21
  30. 2022DeltaCNN: End-to-End CNN Inference of Sparse Frame Differences in Videoscited by 18
  31. 2022YOLOV: Making Still Image Object Detectors Great at Video Object Detectioncited by 18
  32. 2022PTSEFormer: Progressive Temporal-Spatial Enhanced TransFormer Towards Video Object Detectioncited by 17
  33. 2022CSFlow: Learning Optical Flow via Cross Strip Correlation for Autonomous Drivingcited by 16
  34. 2021Multi-frame Collaboration for Effective Endoscopic Video Polyp Detection via Spatial-Temporal Feature Transformationcited by 15
  35. 2023Towards Anytime Optical Flow Estimation with Event Camerascited by 15
  36. 2025Exploiting Temporal State Space Sharing for Video Semantic Segmentationcited by 15
  37. 2022AIParsing: Anchor-free Instance-level Human Parsingcited by 14
  38. 2021Improving Video Instance Segmentation via Temporal Pyramid Routingcited by 13

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