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Self-produced Guidance for Weakly-supervised Object Localization

arXiv 1807.08902 ↗First posted 24 Jul 2018cs.CVcited by 72

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Abstract (arXiv)

Weakly supervised methods usually generate localization results based on attention maps produced by classification networks. However, the attention maps exhibit the most discriminative parts of the object which are small and sparse. We propose to generate Self-produced Guidance (SPG) masks which separate the foreground, the object of interest, from the background to provide the classification networks with spatial correlation information of pixels. A stagewise approach is proposed to incorporate high confident object regions to learn the SPG masks. The high confident regions within attention maps are utilized to progressively learn the SPG masks. The masks are then used as an auxiliary pixel-level supervision to facilitate the training of classification networks. Extensive experiments on ILSVRC demonstrate that SPG is effective in producing high-quality object localizations maps. Particularly, the proposed SPG achieves the Top-1 localization error rate of 43.83% on the ILSVRC validation set, which is a new state-of-the-art error rate.

Key facts. Cited by 72 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: 28; 2022: 20; 2023: 13; 2024: 6; 2025: 2; 2026: 3.

72 papers.

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  1. 2021TS-CAM: Token Semantic Coupled Attention Map for Weakly Supervised Object Localizationcited by 122
  2. 2021UniTAB: Unifying Text and Box Outputs for Grounded Vision-Language Modelingcited by 122
  3. 2021Weakly Supervised Object Localization and Detection: A Surveycited by 84
  4. 2021Large-Scale Unsupervised Object Discoverycited by 54
  5. 2021Unveiling the Potential of Structure Preserving for Weakly Supervised Object Localizationcited by 46
  6. 2021Shallow Feature Matters for Weakly Supervised Object Localizationcited by 34
  7. 2021Contrastive Syn-to-Real Generalizationcited by 32
  8. 2024Data-Efficient Operator Learning via Unsupervised Pretraining and In-Context Learningcited by 32
  9. 2021Online Refinement of Low-level Feature Based Activation Map for Weakly Supervised Object Localizationcited by 30
  10. 2021F-CAM: Full Resolution Class Activation Maps via Guided Parametric Upscalingcited by 26
  11. 2022Bridging the Gap between Classification and Localization for Weakly Supervised Object Localizationcited by 25
  12. 2021LCTR: On Awakening the Local Continuity of Transformer for Weakly Supervised Object Localizationcited by 24
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  1. 2021Background Activation Suppression for Weakly Supervised Object Localizationcited by 22
  2. 2022CREAM: Weakly Supervised Object Localization via Class RE-Activation Mappingcited by 21
  3. 2022Weakly Supervised Object Localization via Transformer with Implicit Spatial Calibrationcited by 20
  4. 2023Generative Prompt Model for Weakly Supervised Object Localizationcited by 20
  5. 2021Just Noticeable Difference for Deep Machine Visioncited by 19
  6. 2021Normalization Matters in Weakly Supervised Object Localizationcited by 19
  7. 2022HINT: Hierarchical Neuron Concept Explainercited by 17
  8. 2023Background Activation Suppression for Weakly Supervised Object Localization and Semantic Segmentationcited by 17
  9. 2022Weakly Supervised Object Localization as Domain Adaptioncited by 16
  10. 2021Keep CALM and Improve Visual Feature Attributioncited by 15
  11. 2022ViTOL: Vision Transformer for Weakly Supervised Object Localizationcited by 13
  12. 2022Discriminative Sampling of Proposals in Self-Supervised Transformers for Weakly Supervised Object Localizationcited by 13
  13. 2022Anti-Adversarially Manipulated Attributions for Weakly Supervised Semantic Segmentation and Object Localizationcited by 12
  14. 2022On Label Granularity and Object Localizationcited by 12
  15. 2022TCAM: Temporal Class Activation Maps for Object Localization in Weakly-Labeled Unconstrained Videoscited by 12
  16. 2022A Novel Plug-in Module for Fine-Grained Visual Classificationcited by 11
  17. 2022Re-Attention Transformer for Weakly Supervised Object Localizationcited by 11
  18. 2022Bagging Regional Classification Activation Maps for Weakly Supervised Object Localizationcited by 9
  19. 2022Negative Evidence Matters in Interpretable Histology Image Classificationcited by 8
  20. 2022Fine-Grained Visual Classification using Self Assessment Classifiercited by 8
  21. 2023DiPS: Discriminative Pseudo-Label Sampling with Self-Supervised Transformers for Weakly Supervised Object Localizationcited by 8
  22. 2021DAP: Detection-Aware Pre-training with Weak Supervisioncited by 7
  23. 2021Weakly-supervised High-resolution Segmentation of Mammography Images for Breast Cancer Diagnosiscited by 7
  24. 2022Contrastive learning of Class-agnostic Activation Map for Weakly Supervised Object Localization and Semantic Segmentationcited by 7
  25. 2022Scaling Novel Object Detection with Weakly Supervised Detection Transformerscited by 7
  26. 2023CoLo-CAM: Class Activation Mapping for Object Co-Localization in Weakly-Labeled Unconstrained Videoscited by 7
  27. 2023Spatial-Aware Token for Weakly Supervised Object Localizationcited by 7
  28. 2021Deep Learning for Weakly-Supervised Object Detection and Object Localization: A Surveycited by 6
  29. 2021Background-aware Classification Activation Map for Weakly Supervised Object Localizationcited by 6
  30. 2022Constrained Sampling for Class-Agnostic Weakly Supervised Object Localizationcited by 6
  31. 2021Weakly Supervised Thoracic Disease Localization via Disease Maskscited by 5
  32. 2021Self-Taught Cross-Domain Few-Shot Learning with Weakly Supervised Object Localization and Task-Decompositioncited by 4
  33. 2021SSA: Semantic Structure Aware Inference for Weakly Pixel-Wise Dense Predictions without Costcited by 4
  34. 2022CaFT: Clustering and Filter on Tokens of Transformer for Weakly Supervised Object Localizationcited by 4
  35. 2023Knowledge-guided Causal Intervention for Weakly-supervised Object Localizationcited by 4
  36. 2023Top-Down Framework for Weakly-supervised Grounded Image Captioningcited by 4
  37. 2021MinMaxCAM: Improving object coverage for CAM-basedWeakly Supervised Object Localizationcited by 3
  38. 2023Counterfactual Co-occurring Learning for Bias Mitigation in Weakly-supervised Object Localizationcited by 3

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