mlsanityData to 7 Oct 2026

Co-Salient Object Detection with Co-Representation Purification

arXiv 2303.07670 ↗First posted 14 Mar 2023cs.CVcited by 9

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Abstract (arXiv)

Co-salient object detection (Co-SOD) aims at discovering the common objects in a group of relevant images. Mining a co-representation is essential for locating co-salient objects. Unfortunately, the current Co-SOD method does not pay enough attention that the information not related to the co-salient object is included in the co-representation. Such irrelevant information in the co-representation interferes with its locating of co-salient objects. In this paper, we propose a Co-Representation Purification (CoRP) method aiming at searching noise-free co-representation. We search a few pixel-wise embeddings probably belonging to co-salient regions. These embeddings constitute our co-representation and guide our prediction. For obtaining purer co-representation, we use the prediction to iteratively reduce irrelevant embeddings in our co-representation. Experiments on three datasets demonstrate that our CoRP achieves state-of-the-art performances on the benchmark datasets. Our source code is available at https://github.com/ZZY816/CoRP.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 29 of its 67 references that are in the map. First posted on arXiv 14 Mar 2023.

Builds on

29 of 67 references.

References · 29

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17 more
  1. 2020Suppress and Balance: A Simple Gated Network for Salient Object Detectioncited by 126
  2. 2020Global Context-Aware Progressive Aggregation Network for Salient Object Detectioncited by 109
  3. 2014Salient Object Detection: A Surveycited by 98
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  7. 2020Re-thinking Co-Salient Object Detectioncited by 54
  8. 2020Gradient-Induced Co-Saliency Detectioncited by 39
  9. 2018Deep Object Co-Segmentationcited by 35
  10. 2020Adaptive Graph Convolutional Network with Attention Graph Clustering for Co-saliency Detectioncited by 35
  11. 2021Group Collaborative Learning for Co-Salient Object Detectioncited by 32
  12. 2020CoADNet: Collaborative Aggregation-and-Distribution Networks for Co-Salient Object Detectioncited by 30
  13. 2021Summarize and Search: Learning Consensus-aware Dynamic Convolution for Co-Saliency Detectioncited by 24
  14. 2019Show, Match and Segment: Joint Weakly Supervised Learning of Semantic Matching and Object Co-segmentationcited by 20
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 4; 2024: 2; 2025: 2; 2026: 1.

9 papers.

  1. 2023Advancing Referring Expression Segmentation Beyond Single Imagecited by 16
  2. 2023Unsupervised and semi-supervised co-salient object detection via segmentation frequency statisticscited by 7
  3. 2023Co-Salient Object Detection with Semantic-Level Consensus Extraction and Dispersioncited by 6
  4. 2023Zero-Shot Co-salient Object Detection Frameworkcited by 4
  5. 2024Representation Purification for End-to-End Speech Translationcited by 3
  6. 2025Visual Consensus Prompting for Co-Salient Object Detectioncited by 3
  7. 2024Self-supervised co-salient object detection via feature correspondence at multiple scalescited by 1
  8. 2025Aesthetic Image Captioning with Saliency Enhanced MLLMscited by 0
  9. 2026Rank-Consistent Set Reasoning for Co-Salient Object Detectioncited by 0