SAM struggles in concealed scenes — empirical study on “Segment Anything”
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Cites
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Self-citationAnabranch network for camouflaged object segmentation
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Flagged first, then by citations
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Cited by
Sorted by citations
Segment anything in medical images
Ma, J., He, Y., Li, F., Han, L., You, C., & Wang, B. (2024) · Nature Communications · doi:10.1038/s41467-024-44824-z · Cited by 2,913 · see citing works
Segment anything model for medical images?
Huang, Y., Yang, X., Liu, L., Zhou, H., Chang, A., Zhou, X., Chen, R., Yu, J., Chen, J., Chen, C., et al. (2024) · Medical Image Analysis · doi:10.1016/j.media.2023.103061 · Cited by 536 · see citing works
“[7] assessed the SAM under the everything mode in segmenting the lesion regions in various anatomical structures (e.”
InfluentialSelf-citationSegment Anything in Medical Images
Ma, J., He, Y., Li, F., Han, L., You, C., & Wang, B. (2023) · arXiv · doi:10.48550/arxiv.2304.12306 · Cited by 67 · see citing works
The Potential of “Segment Anything” (SAM) for Universal Intelligent Ultrasound Image Guidance
Ning, G., Liang, H., Jiang, Z., Zhang, H., & Liao, H. (2023) · BioScience Trends · doi:10.5582/bst.2023.01119 · Cited by 17 · see citing works
- Authors
- Ji, G.-P., Fan, D.-P., Xu, P., Zhou, B., Cheng, M.-M., & Van Gool, L.
- Affiliations
- Australian National University (AU)
- ETH Zurich (CH)
- Tsinghua University (CN)
- Nankai University (CN)
- Corresponding author
- Xu, Peng
- Venue
- Science China Information Sciences
- Published
- 2023-11-08
- Volume
- 66
- Issue
- 12
- ISSN
- 1869-1919 (ISSN-L)
- 1674-733X
- OpenAlex
- W4388574886
- Cited by
- 101
- References
- 12
- Citations by year
- 2026: 15 · 2025: 35 · 2024: 32 · 2023: 19
- FWCI
- 9.18
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- Locations
- Science China Information Sciences (publishedVersion)
- arXiv (Cornell University) (submittedVersion, cc-by)
- arXiv (Cornell University) (cc-by)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Domain Adaptation and Few-Shot Learning
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
- Keywords
- Segment Anything Model, image segmentation, visual grounding, foundation models
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