Papers
DarkSAM: Fooling Segment Anything Model to Segment Nothing
Ziqi Zhou, Yufei Song, Minghui Li et al.
MemSAM: Taming Segment Anything Model for Echocardiography Video Segmentation
Xiaolong Deng, Huisi Wu, Runhao Zeng et al.
From SAM to CAMs: Exploring Segment Anything Model for Weakly Supervised Semantic Segmentation
Hyeokjun Kweon, Kuk-Jin Yoon
GoodSAM: Bridging Domain and Capacity Gaps via Segment Anything Model for Distortion-aware Panoramic Semantic Segmentation
Weiming Zhang, Yexin Liu, Xu Zheng et al.
SAMFlow: Eliminating Any Fragmentation in Optical Flow with Segment Anything Model
Shili Zhou, Ruian He, Weimin Tan et al.
UV-SAM: Adapting Segment Anything Model for Urban Village Identification
Xin Zhang, Yu Liu, Yuming Lin et al.
Parameter Efficient Fine-tuning via Cross Block Orchestration for Segment Anything Model
Zelin Peng, Zhengqin Xu, Zhilin Zeng et al.
AlignSAM: Aligning Segment Anything Model to Open Context via Reinforcement Learning
Duojun Huang, Xinyu Xiong, Jie Ma et al.
BA-SAM: Scalable Bias-Mode Attention Mask for Segment Anything Model
Yiran Song, Qianyu Zhou, Xiangtai Li et al.
ASAM: Boosting Segment Anything Model with Adversarial Tuning
Bo Li, Haoke Xiao, Lv Tang
UnSAMFlow: Unsupervised Optical Flow Guided by Segment Anything Model
Shuai Yuan, Lei Luo, Zhuo Hui et al.
SAM-6D: Segment Anything Model Meets Zero-Shot 6D Object Pose Estimation
Jiehong Lin, Lihua Liu, Dekun Lu et al.
Personalize Segment Anything Model with One Shot
Renrui Zhang, Zhengkai Jiang, Ziyu Guo et al.
Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model
Zihan Zhong, Zhiqiang Tang, Tong He et al.