SegGPT Meets Co-Saliency Scene
Not on the map. Why?
Abstract (arXiv)
Co-salient object detection targets at detecting co-existed salient objects among a group of images. Recently, a generalist model for segmenting everything in context, called SegGPT, is gaining public attention. In view of its breakthrough for segmentation, we can hardly wait to probe into its contribution to the task of co-salient object detection. In this report, we first design a framework to enable SegGPT for the problem of co-salient object detection. Proceed to the next step, we evaluate the performance of SegGPT on the problem of co-salient object detection on three available datasets. We achieve a finding that co-saliency scenes challenges SegGPT due to context discrepancy within a group of co-saliency images.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 12 of its 18 references that are in the map. First posted on arXiv 8 May 2023.
Builds on
12 of 18 references.
References · 12
- 2017Structure-measure: A New Way to Evaluate Foreground Mapscited by 480
- 2018Enhanced-alignment Measure for Binary Foreground Map Evaluationcited by 370
- 2023SegGPT: Segmenting Everything In Contextcited by 193
- 2019Salient Object Detection in the Deep Learning Era: An In-Depth Surveycited by 163
- 2021Salient Object Detection via Integrity Learningcited by 133
- 2015Salient Object Detection: A Benchmarkcited by 130
- 2020Re-thinking Co-Salient Object Detectioncited by 54
- 2020Gradient-Induced Co-Saliency Detectioncited by 39
- 2021Group Collaborative Learning for Co-Salient Object Detectioncited by 32
- 2021Summarize and Search: Learning Consensus-aware Dynamic Convolution for Co-Saliency Detectioncited by 24
- 2022Democracy Does Matter: Comprehensive Feature Mining for Co-Salient Object Detectioncited by 18
- 2023Discriminative Co-Saliency and Background Mining Transformer for Co-Salient Object Detectioncited by 12
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