

Gensam
Overview :
GenSAM is a method for camouflage object detection (COD) that utilizes Cross-modal Chains of Thought Prompting (CCTP) technology to understand visual prompts and leverages general text prompts to obtain reliable visual prompts. The method achieves efficient and accurate camouflage object segmentation through progressive masking generation (PMG) during testing, automatically generating and optimizing visual prompts without additional training.
Target Users :
Suitable for researchers and developers who need to conduct research on camouflage target detection.
Use Cases
Researchers use GenSAM to automatically identify camouflage animals.
Developers apply GenSAM in outdoor surveillance systems for camouflage target detection.
AI enthusiasts use GenSAM to design personalized camouflage patterns.
Features
Camouflage target detection using general text prompts
CCTP technology parsing visual prompts
Automatic optimization of visual prompts during testing
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