A comprehensive survey on segment anything model for vision and beyond

C Zhang, L Liu, Y Cui, G Huang, W Lin, Y Yang… - ar**
C He, K Li, Y Zhang, G Xu, L Tang… - Advances in …, 2024 - proceedings.neurips.cc
Abstract Weakly-Supervised Concealed Object Segmentation (WSCOS) aims to segment
objects well blended with surrounding environments using sparsely-annotated data for …

Explicit visual prompting for low-level structure segmentations

W Liu, X Shen, CM Pun, X Cun - Proceedings of the IEEE …, 2023 - openaccess.thecvf.com
We consider the generic problem of detecting low-level structures in images, which includes
segmenting the manipulated parts, identifying out-of-focus pixels, separating shadow …

SAM Fails to Segment Anything?--SAM-Adapter: Adapting SAM in Underperformed Scenes: Camouflage, Shadow, Medical Image Segmentation, and More

T Chen, L Zhu, C Ding, R Cao, Y Wang, Z Li… - arxiv preprint arxiv …, 2023 - arxiv.org
The emergence of large models, also known as foundation models, has brought significant
advancements to AI research. One such model is Segment Anything (SAM), which is …

Detecting camouflaged object in frequency domain

Y Zhong, B Li, L Tang, S Kuang… - Proceedings of the …, 2022 - openaccess.thecvf.com
Camouflaged object detection (COD) aims to identify objects that are perfectly embedded in
their environment, which has various downstream applications in fields such as medicine …