mlsanityData to 14 Oct 2026

DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision

arXiv 2105.06464 ↗First posted 13 May 2021cs.CV cs.LGcited by 59

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Abstract (arXiv)

We introduce DiscoBox, a novel framework that jointly learns instance segmentation and semantic correspondence using bounding box supervision. Specifically, we propose a self-ensembling framework where instance segmentation and semantic correspondence are jointly guided by a structured teacher in addition to the bounding box supervision. The teacher is a structured energy model incorporating a pairwise potential and a cross-image potential to model the pairwise pixel relationships both within and across the boxes. Minimizing the teacher energy simultaneously yields refined object masks and dense correspondences between intra-class objects, which are taken as pseudo-labels to supervise the task network and provide positive/negative correspondence pairs for dense constrastive learning. We show a symbiotic relationship where the two tasks mutually benefit from each other. Our best model achieves 37.9% AP on COCO instance segmentation, surpassing prior weakly supervised methods and is competitive to supervised methods. We also obtain state of the art weakly supervised results on PASCAL VOC12 and PF-PASCAL with real-time inference.

Key facts. Cited by 59 papers in the map (data through 14 Oct 2026). Builds on 65 of its 99 references that are in the map. First posted on arXiv 13 May 2021.

Builds on

65 of 99 references.

References · 65

  1. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
  2. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,639
  3. 2019Momentum Contrast for Unsupervised Visual Representation Learningcited by 7,513
  4. 2017Mask R-CNNcited by 7,277
  5. 2016Feature Pyramid Networks for Object Detectioncited by 5,036
  6. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,852
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  9. 2020FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidencecited by 2,085
  10. 2019FCOS: Fully Convolutional One-Stage Object Detectioncited by 1,577
  11. 2019SuperGlue: Learning Feature Matching with Graph Neural Networkscited by 1,443
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38 more
  1. 2019Objects as Pointscited by 1,175
  2. 2019EfficientDet: Scalable and Efficient Object Detectioncited by 1,020
  3. 2017How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)cited by 525
  4. 2019YOLACT: Real-time Instance Segmentationcited by 443
  5. 2016ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentationcited by 331
  6. 2018Learning Pixel-level Semantic Affinity with Image-level Supervision for Weakly Supervised Semantic Segmentationcited by 321
  7. 2018Learning Category-Specific Mesh Reconstruction from Image Collectionscited by 317
  8. 2020Conditional Convolutions for Instance Segmentationcited by 314
  9. 2016LIFT: Learned Invariant Feature Transformcited by 306
  10. 2015What's the Point: Semantic Segmentation with Point Supervisioncited by 298
  11. 2019Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relationscited by 247
  12. 2018Deep Object Pose Estimation for Semantic Robotic Grasping of Household Objectscited by 241
  13. 2015BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentationcited by 238
  14. 2016Simple Does It: Weakly Supervised Instance and Semantic Segmentationcited by 227
  15. 2015Weakly- and Semi-Supervised Learning of a DCNN for Semantic Image Segmentationcited by 189
  16. 2019PolarMask: Single Shot Instance Segmentation with Polar Representationcited by 188
  17. 2015Weakly Supervised Deep Detection Networkscited by 183
  18. 2018Neighbourhood Consensus Networkscited by 174
  19. 2014Simultaneous Detection and Segmentationcited by 159
  20. 2018LF-Net: Learning Local Features from Imagescited by 151
  21. 2020BoxInst: High-Performance Instance Segmentation with Box Annotationscited by 151
  22. 2019SPair-71k: A Large-scale Benchmark for Semantic Correspondencecited by 146
  23. 2020Mining Cross-Image Semantics for Weakly Supervised Semantic Segmentationcited by 144
  24. 2017Convolutional neural network architecture for geometric matchingcited by 138
  25. 2020Self-supervised Single-view 3D Reconstruction via Semantic Consistencycited by 127
  26. 2016Fully Convolutional Instance-aware Semantic Segmentationcited by 123
  27. 2015Instance-aware Semantic Segmentation via Multi-task Network Cascadescited by 121
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  30. 2018Learning random-walk label propagation for weakly-supervised semantic segmentationcited by 101
  31. 2019SCOPS: Self-Supervised Co-Part Segmentationcited by 100
  32. 2019Box-driven Class-wise Region Masking and Filling Rate Guided Loss for Weakly Supervised Semantic Segmentationcited by 98
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  34. 2019YOLACT++: Better Real-time Instance Segmentationcited by 84
  35. 2016Universal Correspondence Networkcited by 82
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  38. 2019Canonical Surface Mapping via Geometric Cycle Consistencycited by 63

50 most cited of 65 All 65 (JSON)

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Citing papers per year: 2021: 1; 2022: 13; 2023: 20; 2024: 11; 2025: 9; 2026: 5.

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  1. 2023A Simple Framework for Open-Vocabulary Segmentation and Detectioncited by 198
  2. 2023Transformer-Based Visual Segmentation: A Surveycited by 124
  3. 2022FreeSOLO: Learning to Segment Objects without Annotationscited by 102
  4. 2022BigDatasetGAN: Synthesizing ImageNet with Pixel-wise Annotationscited by 99
  5. 2022MinVIS: A Minimal Video Instance Segmentation Framework without Video-based Trainingcited by 94
  6. 2021Open-Vocabulary Instance Segmentation via Robust Cross-Modal Pseudo-Labelingcited by 84
  7. 2023Visual In-Context Promptingcited by 52
  8. 2024Not All Voxels Are Equal: Hardness-Aware Semantic Scene Completion with Self-Distillationcited by 43
  9. 2022Box-supervised Instance Segmentation with Level Set Evolutioncited by 41
  10. 2023BEVNeXt: Reviving Dense BEV Frameworks for 3D Object Detectioncited by 35
  11. 2022Learning Semantic Correspondence with Sparse Annotationscited by 31
  12. 2022BoxTeacher: Exploring High-Quality Pseudo Labels for Weakly Supervised Instance Segmentationcited by 31
38 more
  1. 2023DaTaSeg: Taming a Universal Multi-Dataset Multi-Task Segmentation Modelcited by 31
  2. 2023Semantic Image Segmentation: Two Decades of Researchcited by 27
  3. 2023Point2Mask: Point-supervised Panoptic Segmentation via Optimal Transportcited by 24
  4. 2022Box2Mask: Box-supervised Instance Segmentation via Level-set Evolutioncited by 22
  5. 2023Mask-Free Video Instance Segmentationcited by 20
  6. 2023Mask-free OVIS: Open-Vocabulary Instance Segmentation without Manual Mask Annotationscited by 16
  7. 2023Semantic-aware SAM for Point-Prompted Instance Segmentationcited by 16
  8. 2022Active Pointly-Supervised Instance Segmentationcited by 15
  9. 2023Vision Transformers Are Good Mask Auto-Labelerscited by 14
  10. 2024MultiverSeg: Scalable Interactive Segmentation of Biomedical Imaging Datasets with In-Context Guidancecited by 13
  11. 2025Do It Yourself: Learning Semantic Correspondence from Pseudo-Labelscited by 13
  12. 2023BoxSnake: Polygonal Instance Segmentation with Box Supervisioncited by 12
  13. 2023SIM: Semantic-aware Instance Mask Generation for Box-Supervised Instance Segmentationcited by 11
  14. 2022LWSIS: LiDAR-guided Weakly Supervised Instance Segmentation for Autonomous Drivingcited by 9
  15. 2023Label-efficient Segmentation via Affinity Propagationcited by 7
  16. 2024UVCPNet: A UAV-Vehicle Collaborative Perception Network for 3D Object Detectioncited by 7
  17. 2022BoxMask: Revisiting Bounding Box Supervision for Video Object Detectioncited by 6
  18. 2023GaPro: Box-Supervised 3D Point Cloud Instance Segmentation Using Gaussian Processes as Pseudo Labelerscited by 6
  19. 2024What is Point Supervision Worth in Video Instance Segmentation?cited by 5
  20. 2025G4Seg: Generation for Inexact Segmentation Refinement with Diffusion Modelscited by 5
  21. 2022Box Supervised Video Segmentation Proposal Networkcited by 4
  22. 2024Fine-grained Background Representation for Weakly Supervised Semantic Segmentationcited by 4
  23. 2025Learning 3D Scene Analogies with Neural Contextual Scene Mapscited by 4
  24. 2025Sketchy Bounding-box Supervision for 3D Instance Segmentationcited by 4
  25. 2022AsyInst: Asymmetric Affinity with DepthGrad and Color for Box-Supervised Instance Segmentationcited by 3
  26. 2024Extreme Point Supervised Instance Segmentationcited by 3
  27. 2025Advancing Visual Large Language Model for Multi-granular Versatile Perceptioncited by 3
  28. 2025Towards Geometry-Grounded Dense Semantic Matching with VGGT Priorscited by 3
  29. 2023IBoxCLA: Towards Robust Box-supervised Segmentation of Polyp via Improved Box-dice and Contrastive Latent-anchorscited by 2
  30. 2024Boosting Box-supervised Instance Segmentation with Pseudo Depthcited by 2
  31. 2024PM-VIS: High-Performance Box-Supervised Video Instance Segmentationcited by 2
  32. 2025Generalized Class Discovery in Instance Segmentationcited by 2
  33. 2023PWISeg: Point-based Weakly-supervised Instance Segmentation for Surgical Instrumentscited by 1
  34. 2025Towards Optimal Heterogeneous Client Sampling in Multi-Model Federated Learningcited by 1
  35. 2022WUDA: Unsupervised Domain Adaptation Based on Weak Source Domain Labelscited by 0
  36. 2023BoxVIS: Video Instance Segmentation with Box Annotationscited by 0
  37. 2023Synthetic Instance Segmentation from Semantic Image Segmentation Maskscited by 0
  38. 2023Efficient Segmentation with Texture in Ore Images Based on Box-supervised Approachcited by 0

50 most cited of 59 All 59 (JSON)