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PReMVOS: Proposal-generation, Refinement and Merging for Video Object Segmentation

arXiv 1807.09190 ↗First posted 24 Jul 2018cs.CVcited by 81

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Abstract (arXiv)

We address semi-supervised video object segmentation, the task of automatically generating accurate and consistent pixel masks for objects in a video sequence, given the first-frame ground truth annotations. Towards this goal, we present the PReMVOS algorithm (Proposal-generation, Refinement and Merging for Video Object Segmentation). Our method separates this problem into two steps, first generating a set of accurate object segmentation mask proposals for each video frame and then selecting and merging these proposals into accurate and temporally consistent pixel-wise object tracks over a video sequence in a way which is designed to specifically tackle the difficult challenges involved with segmenting multiple objects across a video sequence. Our approach surpasses all previous state-of-the-art results on the DAVIS 2017 video object segmentation benchmark with a J & F mean score of 71.6 on the test-dev dataset, and achieves first place in both the DAVIS 2018 Video Object Segmentation Challenge and the YouTube-VOS 1st Large-scale Video Object Segmentation Challenge.

Key facts. Cited by 81 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Jul 2018.

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Citing papers per year: 2021: 32; 2022: 23; 2023: 13; 2024: 7; 2025: 2; 2026: 4.

81 papers.

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  1. 2021Conditional Object-Centric Learning from Videocited by 247
  2. 2021Associating Objects with Transformers for Video Object Segmentationcited by 225
  3. 2021Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentationcited by 200
  4. 2022Decoupling Features in Hierarchical Propagation for Video Object Segmentationcited by 146
  5. 2021Modular Interactive Video Object Segmentation: Interaction-to-Mask, Propagation and Difference-Aware Fusioncited by 129
  6. 2021SSTVOS: Sparse Spatiotemporal Transformers for Video Object Segmentationcited by 106
  7. 2021STEP: Segmenting and Tracking Every Pixelcited by 72
  8. 2021Hierarchical Memory Matching Network for Video Object Segmentationcited by 72
  9. 2021MOTSynth: How Can Synthetic Data Help Pedestrian Detection and Tracking?cited by 68
  10. 2021SwiftNet: Real-time Video Object Segmentationcited by 67
  11. 20214D Panoptic LiDAR Segmentationcited by 64
  12. 2021Learning Position and Target Consistency for Memory-based Video Object Segmentationcited by 63
38 more
  1. 2021Joint Inductive and Transductive Learning for Video Object Segmentationcited by 61
  2. 2022Recurrent Dynamic Embedding for Video Object Segmentationcited by 52
  3. 2021Opening up Open-World Trackingcited by 50
  4. 2023Self-supervised Object-Centric Learning for Videoscited by 49
  5. 2022Breaking the "Object" in Video Object Segmentationcited by 48
  6. 2022Per-Clip Video Object Segmentationcited by 40
  7. 2021Reliable Propagation-Correction Modulation for Video Object Segmentationcited by 36
  8. 2022Learning Quality-aware Dynamic Memory for Video Object Segmentationcited by 35
  9. 2023Scalable Video Object Segmentation with Simplified Frameworkcited by 29
  10. 2021Dense Unsupervised Learning for Video Segmentationcited by 26
  11. 2022Locality-Aware Inter-and Intra-Video Reconstruction for Self-Supervised Correspondence Learningcited by 26
  12. 2022SWEM: Towards Real-Time Video Object Segmentation with Sequential Weighted Expectation-Maximizationcited by 26
  13. 2022Global Spectral Filter Memory Network for Video Object Segmentationcited by 22
  14. 2021HODOR: High-level Object Descriptors for Object Re-segmentation in Video Learned from Static Imagescited by 21
  15. 2021D^2Conv3D: Dynamic Dilated Convolutions for Object Segmentation in Videoscited by 20
  16. 2022Scalable Video Object Segmentation with Identification Mechanismcited by 18
  17. 2022Region Aware Video Object Segmentation with Deep Motion Modelingcited by 18
  18. 2023PanoVOS: Bridging Non-panoramic and Panoramic Views with Transformer for Video Segmentationcited by 18
  19. 2023MobileVOS: Real-Time Video Object Segmentation Contrastive Learning meets Knowledge Distillationcited by 16
  20. 2021TransVOS: Video Object Segmentation with Transformerscited by 15
  21. 2023Tracking through Containers and Occluders in the Wildcited by 15
  22. 2024Temporally Consistent Referring Video Object Segmentation with Hybrid Memorycited by 14
  23. 2021Self-Supervised Video Object Segmentation by Motion-Aware Mask Propagationcited by 11
  24. 2021Pixel-Level Bijective Matching for Video Object Segmentationcited by 11
  25. 2021Siamese Network with Interactive Transformer for Video Object Segmentationcited by 11
  26. 2022Siamese Object Tracking for Unmanned Aerial Vehicle: A Review and Comprehensive Analysiscited by 11
  27. 2022Towards Robust Video Object Segmentation with Adaptive Object Calibrationcited by 11
  28. 2021Accelerating Video Object Segmentation with Compressed Videocited by 10
  29. 2021Generating Masks from Boxes by Mining Spatio-Temporal Consistencies in Videoscited by 8
  30. 2022Resolving label uncertainty with implicit posterior modelscited by 8
  31. 2021MUNet: Motion Uncertainty-aware Semi-supervised Video Object Segmentationcited by 7
  32. 2023Two-shot Video Object Segmentationcited by 7
  33. 2024Learning Spatial-Semantic Features for Robust Video Object Segmentationcited by 7
  34. 2021MSN: Efficient Online Mask Selection Network for Video Instance Segmentationcited by 6
  35. 2022DirectTracker: 3D Multi-Object Tracking Using Direct Image Alignment and Photometric Bundle Adjustmentcited by 6
  36. 2022Learning to Learn Better for Video Object Segmentationcited by 6
  37. 2021Breaking Shortcut: Exploring Fully Convolutional Cycle-Consistency for Video Correspondence Learningcited by 5
  38. 2022Transfer of Representations to Video Label Propagation: Implementation Factors Mattercited by 5

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