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Black-box targeted adversarial attack on segment anything (sam)
Deep recognition models are widely vulnerable to adversarial examples, which change the
model output by adding quasi-imperceptible perturbation to the image input. Recently …
model output by adding quasi-imperceptible perturbation to the image input. Recently …
Fastsam3d: An efficient segment anything model for 3d volumetric medical images
Segment anything models (SAMs) are gaining attention for their zero-shot generalization
capability in segmenting objects of unseen classes and in unseen domains when properly …
capability in segmenting objects of unseen classes and in unseen domains when properly …
Esp-medsam: Efficient self-prompting sam for universal domain-generalized medical image segmentation
Constraint-Aware Zero-Shot Vision-Language Navigation in Continuous Environments
We address the task of Vision-Language Navigation in Continuous Environments (VLN-CE)
under the zero-shot setting. Zero-shot VLN-CE is particularly challenging due to the absence …
under the zero-shot setting. Zero-shot VLN-CE is particularly challenging due to the absence …
Swiss Army Knife: Synergizing Biases in Knowledge from Vision Foundation Models for Multi-Task Learning
Vision Foundation Models (VFMs) have demonstrated outstanding performance on
numerous downstream tasks. However, due to their inherent representation biases …
numerous downstream tasks. However, due to their inherent representation biases …
EdgeTAM: On-Device Track Anything Model
On top of Segment Anything Model (SAM), SAM 2 further extends its capability from image to
video inputs through a memory bank mechanism and obtains a remarkable performance …
video inputs through a memory bank mechanism and obtains a remarkable performance …
[HTML][HTML] An Efficient Group Convolution and Feature Fusion Method for Weed Detection
C Chen, Y Zang, J Jiao, D Yan, Z Fan, Z Cui, M Zhang - Agriculture, 2024 - mdpi.com
Weed detection is a crucial step in achieving intelligent weeding for vegetables. Currently,
research on vegetable weed detection technology is relatively limited, and existing detection …
research on vegetable weed detection technology is relatively limited, and existing detection …