mlsanityData to 7 Oct 2026

Deep Learning for Weakly-Supervised Object Detection and Object Localization: A Survey

arXiv 2105.12694 ↗First posted 26 May 2021cs.CVcited by 6

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Abstract (arXiv)

Weakly-Supervised Object Detection (WSOD) and Localization (WSOL), i.e., detecting multiple and single instances with bounding boxes in an image using image-level labels, are long-standing and challenging tasks in the CV community. With the success of deep neural networks in object detection, both WSOD and WSOL have received unprecedented attention. Hundreds of WSOD and WSOL methods and numerous techniques have been proposed in the deep learning era. To this end, in this paper, we consider WSOL is a sub-task of WSOD and provide a comprehensive survey of the recent achievements of WSOD. Specifically, we firstly describe the formulation and setting of the WSOD, including the background, challenges, basic framework. Meanwhile, we summarize and analyze all advanced techniques and training tricks for improving detection performance. Then, we introduce the widely-used datasets and evaluation metrics of WSOD. Lastly, we discuss the future directions of WSOD. We believe that these summaries can help pave a way for future research on WSOD and WSOL.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 59 of its 90 references that are in the map. First posted on arXiv 26 May 2021.

Builds on

59 of 90 references.

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38 more
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50 most cited of 59 All 59 (JSON)

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Cited by year

Citing papers per year: 2021: 1; 2022: 1; 2023: 2; 2024: 1; 2025: 1.

6 papers.

  1. 2021Few-Shot Object Detection: A Comprehensive Surveycited by 28
  2. 2022Optical Remote Sensing Image Understanding with Weak Supervision: Concepts, Methods, and Perspectivescited by 6
  3. 2023A Large-Scale Analysis on Self-Supervised Video Representation Learningcited by 5
  4. 2025A Large-Scale Analysis on Contextual Self-Supervised Video Representation Learningcited by 3
  5. 2024WEEP: A method for spatial interpretation of weakly supervised CNN models in computational pathologycited by 1
  6. 2023Identifying Light-curve Signals with a Deep Learning Based Object Detection Algorithm. II. A General Light Curve Classification Frameworkcited by 0