mlsanityData to 14 Oct 2026

Bounding Box Tightness Prior for Weakly Supervised Image Segmentation

arXiv 2110.00934 ↗First posted 3 Oct 2021cs.CV cs.AIcited by 19

Not on the map. Why?

Abstract (arXiv)

This paper presents a weakly supervised image segmentation method that adopts tight bounding box annotations. It proposes generalized multiple instance learning (MIL) and smooth maximum approximation to integrate the bounding box tightness prior into the deep neural network in an end-to-end manner. In generalized MIL, positive bags are defined by parallel crossing lines with a set of different angles, and negative bags are defined as individual pixels outside of any bounding boxes. Two variants of smooth maximum approximation, i.e., α-softmax function and α-quasimax function, are exploited to conquer the numeral instability introduced by maximum function of bag prediction. The proposed approach was evaluated on two pubic medical datasets using Dice coefficient. The results demonstrate that it outperforms the state-of-the-art methods. The codes are available at urlhttps://github.com/wangjuan313/wsis-boundingbox.

Key facts. Cited by 19 papers in the map (data through 14 Oct 2026). Builds on 13 of its 21 references that are in the map. First posted on arXiv 3 Oct 2021.

Builds on

13 of 21 references.

References · 13

  1. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  3. 2014Fully Convolutional Networks for Semantic Segmentationcited by 4,859
  4. 2018Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentationcited by 3,223
  5. 2016ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentationcited by 331
  6. 2020Self-supervised Equivariant Attention Mechanism for Weakly Supervised Semantic Segmentationcited by 300
  7. 2015What's the Point: Semantic Segmentation with Point Supervisioncited by 298
  8. 2016ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentationcited by 291
  9. 2019Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relationscited by 247
  10. 2016Simple Does It: Weakly Supervised Instance and Semantic Segmentationcited by 227
  11. 2015Multiscale Combinatorial Grouping for Image Segmentation and Object Proposal Generationcited by 91
  12. 2016DeepCut: Object Segmentation from Bounding Box Annotations using Convolutional Neural Networkscited by 79
1 more
  1. 2020Bounding boxes for weakly supervised segmentation: Global constraints get close to full supervisioncited by 40

Built on by

Cited by year

Citing papers per year: 2022: 3; 2023: 5; 2024: 8; 2025: 3.

19 papers.

Sort:

  1. 2023Label-Efficient Deep Learning in Medical Image Analysis: Challenges and Future Directionscited by 16
  2. 2024BoNuS: Boundary Mining for Nuclei Segmentation with Partial Point Labelscited by 8
  3. 2023Data efficient deep learning for medical image analysis: A surveycited by 6
  4. 2024FedLPPA: Learning Personalized Prompt and Aggregation for Federated Weakly-supervised Medical Image Segmentationcited by 6
  5. 2024MonoBox: Tightness-free Box-supervised Polyp Segmentation using Monotonicity Constraintcited by 5
  6. 2024Automating MedSAM by Learning Prompts with Weak Few-Shot Supervisioncited by 5
  7. 2024Beyond Pixel-Wise Supervision for Medical Image Segmentation: From Traditional Models to Foundation Modelscited by 4
  8. 2023Weakly Supervised Image Segmentation Beyond Tight Bounding Box Annotationscited by 3
  9. 2024From Few to More: Scribble-based Medical Image Segmentation via Masked Context Modeling and Continuous Pseudo Labelscited by 3
  10. 2025COIN: Confidence Score-Guided Distillation for Annotation-Free Cell Segmentationcited by 3
  11. 2023IBoxCLA: Towards Robust Box-supervised Segmentation of Polyp via Improved Box-dice and Contrastive Latent-anchorscited by 2
  12. 2024OOD-SEG: Exploiting out-of-distribution detection techniques for learning image segmentation from sparse multi-class positive-only annotationscited by 2
7 more
  1. 2025Prompt learning with bounding box constraints for medical image segmentationcited by 2
  2. 2022Polar Transformation Based Multiple Instance Learning Assisting Weakly Supervised Image Segmentation With Loose Bounding Box Annotationscited by 1
  3. 2022Cardiac Adipose Tissue Segmentation via Image-Level Annotationscited by 1
  4. 2023BoxCell: Leveraging SAM for Cell Segmentation with Box Supervisioncited by 1
  5. 2024Weakly-Supervised Learning via Multi-Lateral Decoder Branching for Tool Segmentation in Robot-Assisted Cardiovascular Catheterizationcited by 1
  6. 2022Coarse Retinal Lesion Annotations Refinement via Prototypical Learningcited by 0
  7. 2025Label tree semantic losses for rich multi-class medical image segmentationcited by 0