DFA-CON: A Contrastive Learning Approach for Detecting Copyright Infringement in DeepFake Art
专题命中 图像生成评测 :inpainting(abstract);分类 cs.CV
视觉与机器人
图像生成、文生图、图像编辑、扩散模型和可控生成。
专题命中 图像生成评测 :inpainting(abstract);分类 cs.CV
机构 * Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University(图像通信与网络工程研究所,上海交通大学)
专题命中 图像生成评测 :text-to-image(abstract);分类 cs.CV
机构 * Rapid-Rich Object Search Lab, School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore(快速丰富目标搜索实验室,电气与电子工程学院,南洋理工大学,新加坡) ; Rapid-Rich Object Search Lab, Interdisciplinary Graduate Programme, Nanyang Technological University, Singapore(快速丰富目标搜索实验室,跨学科研究生项目,南洋理工大学,新加坡) ; Pengcheng Laboratory, Shenzhen, China(鹏城实验室,深圳,中国) ; Institute of Big Data, Fudan University, Shanghai, China(大数据研究院,复旦大学,上海,中国)
专题命中 图像生成评测 :diffusion(abstract);分类 cs.CV
机构 * University of Notre Dame(内布拉斯加大学达灵顿分校) ; Guangdong Provincial People’s Hospital(广东省级人民医院)
专题命中 图像生成评测 :diffusion(abstract);分类 cs.CV
Comments 8 pages, conference
专题命中 图像生成评测 :image synthesis(abstract);分类 cs.CV
Comments Accpeted to Journal of Imaging Informatics in Medicine
机构 * School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University(上海交通大学电子信息与电气工程学院) ; Department of Artificial Intelligence, Xiamen University(厦门大学人工智能系) ; School of Information Science and Technology, Shijiazhuang Tiedao University(石家庄铁道大学信息科学与技术学院) ; Electrical Engineering Department, UCLA(加州大学洛杉矶分校电子工程系) ; New Laboratory of Pattern Recognition(NLPR), Institute of Automation, Chinese Academy of Sciences(中国科学院自动化研究所模式识别新实验室) ; College of Electronics and Information Engineering, Shenzhen University(深圳大学电子与信息工程学院) ; School of Computing and Information Technology, Great Bay University(广东东莞Great Bay大学计算与信息科技学院) ; School of Cyber Science and Technology, Shenzhen Campus of Sun Yat-sen University(中山大学深圳校区网络科学与技术学院)
专题命中 图像生成评测 :diffusion(abstract);分类 cs.CV
Comments Accepted by Visual Intelligence
机构 * Nanjing Tech University(南京理工大学)
专题命中 图像生成评测 :text-to-image(abstract);分类 cs.CV
Comments 9 pages, 8 figures, Proceedings of the 32nd ACM International Conference on Multimedia
Journal ref The 32nd ACM International Conference on Multimedia. 2024: 10105-10113
专题命中 图像生成评测 :diffusion(abstract);分类 cs.CV
Comments 28 pages, 18 figures. Not yet submitted to a journal or conference
专题命中 图像生成评测 :diffusion(abstract);分类 cs.CV
专题命中 图像生成评测 :image generation(abstract);分类 cs.CV
Comments Accepted by CVPR 2025, Highlight
专题命中 图像生成评测 :image generation(abstract);分类 cs.CV
Journal ref ICLR 2025
专题命中 图像生成评测 :image synthesis(abstract);分类 cs.CV
专题命中 图像生成评测 :diffusion(abstract);分类 cs.CV
专题命中 图像生成评测 :diffusion(abstract);分类 cs.CV
专题命中 图像生成评测 :image generation(abstract);分类 cs.CV
专题命中 图像生成评测 :generative vision(abstract);分类 cs.CV
Comments Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2025)
专题命中 图像生成评测 :diffusion(abstract);分类 cs.CV
专题命中 图像生成评测 :diffusion(abstract);分类 cs.CV
Comments Accepted by CVPR 2025 Project webpage: https://mono2stereo-bench.github.io/
专题命中 图像生成评测 :image synthesis(abstract);分类 cs.CV
专题命中 图像生成评测 :diffusion(abstract);分类 cs.CV
Comments IEEE/CVF Computer Vision and Pattern Recognition 2025; 22 pages
专题命中 图像生成评测 :diffusion(abstract);分类 cs.CV
Comments CVPR 2025. Project page: https://snap-research.github.io/open-set-video-personalization/
专题命中 图像生成评测 :diffusion(abstract);分类 cs.CV
专题命中 图像生成评测 :image generation(abstract);分类 cs.CV
Comments Code: https://github.com/PKU-YuanGroup/Next-Patch-Prediction, v2: add related work "Patch-Level Training for Large Language Models", v3: Add content
专题命中 图像生成评测 :diffusion(abstract);分类 cs.CV
Comments Project page: https://ai4ce.github.io/EUVS-Benchmark/
专题命中 图像生成评测 :diffusion(abstract);分类 cs.CV
Comments Accepted to ICRA 2025. Project page: https://deform-pam.robotflow.ai
专题命中 图像生成评测 :diffusion(abstract);分类 cs.CV
专题命中 图像生成评测 :text-to-image(abstract);分类 cs.CV
专题命中 图像生成评测 :diffusion(abstract);分类 cs.CV
专题命中 图像生成评测 :diffusion(abstract);分类 cs.CV
Comments This paper has been accepted by CVPR 2025
专题命中 图像生成评测 :image generation(abstract);分类 cs.CV
Comments We added benchmark results (without updating models) and ablation study in this version. Project released at: https://github.com/AILab-CVC/SEED-X