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...
实验结果显示,PromptAD在1、2和4-shot的少样本设置下,相比于其他传统方法和基于CLIP的方法,如WinCLIP+ 和 RWDA,都有显著的性能提升。特别是在MVTec和VisA数据集上,PromptAD的性能提升百分比在1.3%到2.9%之间,这表明PromptAD在少样本异常检测方面具有强大的能力。此外,PromptAD在实现这些性能提升的同时,使用的提示数...
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...
One-Prompt to Segment All Medical Images. [Paper] [Code] 摘要:大型基础模型以其强大的零样本泛化能力而著称,在视觉和语言应用方面表现出色。然而,将它们应用于医学影像分割领域——一个包含多种成像类型和目标标签的领域,仍然是一个悬而未决的挑战。当前的方法,如调整交互式分割模型(如Segment Anything Model,简...
One Prompt Word is Enough to Boost Adversarial Robustness for Pre-trained Vision-Language Models⭐code SC-Tune: Unleashing Self-Consistent Referential Comprehension in Large Vision Language Models⭐code RegionGPT: Towards Region Understanding Vision Language Model Enhancing Vision-Language Pre-training wi...
Deformable One-shot Face Stylization via DINO Semantic Guidance 作者:周漾(深圳大学),陈子冲(深圳大学),黄惠(深圳大学) 论文简介:针对单样本人脸风格化,本文仅使用一对真实-风格化样例,同时考虑外观和结构的跨域变化。核心是利用自监督DINO-ViT来提取图像特征并...
Multimodal Prompt Perceiver: Empower Adaptiveness, Generalizability and Fidelity for All-in-One Image Restoration 作者:艾雨昂(中国科学院自动化研究所),黄怀波(中国科学院自动化研究所),周晓强(中国科学技术大学),王杰翔(中国科学技术大学),赫然(中国科学院自...
OMG-Seg: Is One Model Good Enough For All Segmentation? Fri 21 Jun 5 p.m. Towards Language-Driven Video Inpainting via Multimodal Large Language Models Thu 20 Jun 10:30 a.m. Symphonize 3D Semantic Scene Completion with Contextual Instance Queries ...
local visual features with these prompts striking a balance between global consensus and local personalization. By relaxing one of the equality constraints FedOTP enables prompts to focus solely on core image patch regions. Extensive experiments on datasets with various types of heterogeneities have ...