Code: https://github.com/LLVM-AD/MAPLM One Prompt Word is Enough to Boost Adversarial Robustness for Pre-trained Vision-Language Models Paper:https://arxiv.org/pdf/2403.01849.pdf Code:https://github.com/TreeLLi/APT PromptKD: Unsupervised Prompt Distillation for Vision-Language Models Paper:http...
Code:https://github.com/LLVM-AD/MAPLM One Prompt Word is Enough to Boost Adversarial Robustness for Pre-trained Vision-Language Models Paper:https://arxiv.org/pdf/2403.01849.pdf Code:https://github.com/TreeLLi/APT PromptKD: Unsupervised Prompt Distillation for Vision-Language Models Paper:https...
Code:https://github.com/LLVM-AD/MAPLM One Prompt Word is Enough to Boost Adversarial Robustness ...
One-Prompt to Segment All Medical Images Junde Wu, Min Xu; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024, pp. 11302-11312 Abstract Large foundation models known for their strong zero-shot generalization have excelled in visual an...
one-class anomaly detection. To address the above problem this paper proposes a one-class prompt learning method for few-shot anomaly detection termed PromptAD. First we propose semantic concatenation which can transpose normal prompts into anomaly prompts by concatenating normal prompts with anomaly...
One-Prompt to Segment All Medical Images, or say One-Prompt, combines the strengths of one-shot and interactive methods. In the inference stage, with just one prompted sample, it can adeptly handle the unseen task in a single forward pass. This method is elaborated in the paper One-Prompt...
Code:https://github.com/zhengli97/PromptKD FairCLIP: Harnessing Fairness in Vision-Language Learning Paper:https://arxiv.org/abs/2403.19949 Code:https://github.com/Harvard-Ophthalmology-AI-Lab/FairCLIP 目标检测(Object Detection) DETRs Beat YOLOs on Real-time Object Detection ...
One Prompt Word is Enough to Boost Adversarial Robustness for Pre-trained Vision-Language Models Paper:https://arxiv.org/pdf/2403.01849.pdf Code:https://github.com/TreeLLi/APT PromptKD: Unsupervised Prompt Distillation for Vision-Language Models Paper:https://arxiv.org/pdf/2403.02781 RegionGPT:...
论文简介:我们提出了随机提示辅助弱监督3D对象检测,称为Prompt3D。这种方法利用位置级标签来克服注释成本高的挑战。我们的方法主要利用由随机提示生成的3D形状制作的合成场景来增强标记。首先,引入了合成场景生成(SSG)模块,合成场景由精选的3D形状根据真实场景的位置...
68、VP3D: Unleashing 2D Visual Prompt for Text-to-3D Generation 关于文本到三维生成的创新推出了得分蒸馏抽样(Score Distillation Sampling,SDS),通过直接从二维扩散模型中提取先验知识,实现隐式三维模型(NeRF)的零样本学习。然而,当前基于SDS的模型在处理复杂的文本提示时仍存在困难,并且通常会导致3D模型出现畸变,...