mlsanityData to 7 Oct 2026

Learning Video Object Segmentation from Static Images

arXiv 1612.02646 ↗First posted 8 Dec 2016cs.CVcited by 151

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Abstract (arXiv)

Inspired by recent advances of deep learning in instance segmentation and object tracking, we introduce video object segmentation problem as a concept of guided instance segmentation. Our model proceeds on a per-frame basis, guided by the output of the previous frame towards the object of interest in the next frame. We demonstrate that highly accurate object segmentation in videos can be enabled by using a convnet trained with static images only. The key ingredient of our approach is a combination of offline and online learning strategies, where the former serves to produce a refined mask from the previous frame estimate and the latter allows to capture the appearance of the specific object instance. Our method can handle different types of input annotations: bounding boxes and segments, as well as incorporate multiple annotated frames, making the system suitable for diverse applications. We obtain competitive results on three different datasets, independently from the type of input annotation.

Key facts. Cited by 151 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Dec 2016.

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Citing papers per year: 2021: 42; 2022: 35; 2023: 26; 2024: 28; 2025: 13; 2026: 7.

151 papers.

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  1. 2024SAM 2: Segment Anything in Images and Videoscited by 2,784
  2. 2022XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Modelcited by 436
  3. 2023MOSE: A New Dataset for Video Object Segmentation in Complex Scenescited by 232
  4. 2021Associating Objects with Transformers for Video Object Segmentationcited by 225
  5. 2021A Survey of Human-in-the-loop for Machine Learningcited by 214
  6. 2021Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentationcited by 200
  7. 2023Putting the Object Back into Video Object Segmentationcited by 182
  8. 2021Occluded Video Instance Segmentation: A Benchmarkcited by 154
  9. 2022Decoupling Features in Hierarchical Propagation for Video Object Segmentationcited by 146
  10. 2021A Survey on Deep Learning Technique for Video Segmentationcited by 132
  11. 2021Modular Interactive Video Object Segmentation: Interaction-to-Mask, Propagation and Difference-Aware Fusioncited by 129
  12. 2021SSTVOS: Sparse Spatiotemporal Transformers for Video Object Segmentationcited by 106
38 more
  1. 2021Efficient Regional Memory Network for Video Object Segmentationcited by 86
  2. 2021Full-Duplex Strategy for Video Object Segmentationcited by 78
  3. 2024SAM2Long: Enhancing SAM 2 for Long Video Segmentation with a Training-Free Memory Treecited by 77
  4. 2022LVOS: A Benchmark for Long-term Video Object Segmentationcited by 76
  5. 2021Video Instance Segmentation with a Propose-Reduce Paradigmcited by 74
  6. 2021Hierarchical Memory Matching Network for Video Object Segmentationcited by 72
  7. 2021SwiftNet: Real-time Video Object Segmentationcited by 67
  8. 2021Learning Position and Target Consistency for Memory-based Video Object Segmentationcited by 63
  9. 2021Joint Inductive and Transductive Learning for Video Object Segmentationcited by 61
  10. 2025MOSEv2: A More Challenging Dataset for Video Object Segmentation in Complex Scenescited by 59
  11. 2021Semantics for Robotic Mapping, Perception and Interaction: A Surveycited by 56
  12. 2022Recurrent Dynamic Embedding for Video Object Segmentationcited by 52
  13. 2024Vivim: a Video Vision Mamba for Medical Video Segmentationcited by 51
  14. 2022Breaking the "Object" in Video Object Segmentationcited by 48
  15. 2022Local-Global Context Aware Transformer for Language-Guided Video Segmentationcited by 41
  16. 2024LVOS: A Benchmark for Large-scale Long-term Video Object Segmentationcited by 41
  17. 2022Per-Clip Video Object Segmentationcited by 40
  18. 2022Robust Visual Tracking by Segmentationcited by 38
  19. 2021Reliable Propagation-Correction Modulation for Video Object Segmentationcited by 36
  20. 2022Learning Quality-aware Dynamic Memory for Video Object Segmentationcited by 35
  21. 2023CLIP-S4: Language-Guided Self-Supervised Semantic Segmentationcited by 34
  22. 2022Look Before You Match: Instance Understanding Matters in Video Object Segmentationcited by 33
  23. 2024Ref-AVS: Refer and Segment Objects in Audio-Visual Scenescited by 32
  24. 2021ORBIT: A Real-World Few-Shot Dataset for Teachable Object Recognitioncited by 29
  25. 2023Scalable Video Object Segmentation with Simplified Frameworkcited by 29
  26. 2022Locality-Aware Inter-and Intra-Video Reconstruction for Self-Supervised Correspondence Learningcited by 26
  27. 2022SWEM: Towards Real-Time Video Object Segmentation with Sequential Weighted Expectation-Maximizationcited by 26
  28. 2021HODOR: High-level Object Descriptors for Object Re-segmentation in Video Learned from Static Imagescited by 21
  29. 2023Boosting Video Object Segmentation via Space-time Correspondence Learningcited by 21
  30. 2024Event-assisted Low-Light Video Object Segmentationcited by 21
  31. 2025EdgeTAM: On-Device Track Anything Modelcited by 21
  32. 2023Learning the What and How of Annotation in Video Object Segmentationcited by 19
  33. 2021Learning to Recommend Frame for Interactive Video Object Segmentation in the Wildcited by 18
  34. 2022Scalable Video Object Segmentation with Identification Mechanismcited by 18
  35. 2022Region Aware Video Object Segmentation with Deep Motion Modelingcited by 18
  36. 2023PanoVOS: Bridging Non-panoramic and Panoramic Views with Transformer for Video Segmentationcited by 18
  37. 2023MobileVOS: Real-Time Video Object Segmentation Contrastive Learning meets Knowledge Distillationcited by 16
  38. 2023Unified Mask Embedding and Correspondence Learning for Self-Supervised Video Segmentationcited by 16

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