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检索条件"任意字段=1994 IEEE Computer-Society Conference on Computer Vision and Pattern Recognition"
22886 条 记 录,以下是241-250 订阅
排序:
GRAM: Global Reasoning for Multi-Page VQA
GRAM: Global Reasoning for Multi-Page VQA
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Blau, Tsachi Fogel, Sharon Ronen, Roi Goltst, Alona Per, Shahar Tsi Ben Avraham, Elad Aberdam, Aviad Ganz, Roy Litman, Ron Technion Haifa Israel AWS AI Labs Shanghai Peoples R China
The increasing use of transformer-based large language models brings forward the challenge of processing long sequences. In document visual question answering (DocVQA), leading methods focus on the single-page setting... 详细信息
来源: 评论
Sequential Modeling Enables Scalable Learning for Large vision Models
Sequential Modeling Enables Scalable Learning for Large Visi...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Bail, Yutong Geng, Xinyang Mangalam, Karttikeya Bar, Amir Yuille, Alan L. Darrell, Trevor Malik, Jitendra Efros, Alexei A. UC Berkeley BAIR Berkeley CA 94720 USA Johns Hopkins Univ Baltimore MD 21218 USA
We introduce a novel sequential modeling approach which enables learning a Large vision Model (LVM) without making use of any linguistic data. To do this, we define a common format, "visual sentences", in wh... 详细信息
来源: 评论
Split to Merge: Unifying Separated Modalities for Unsupervised Domain Adaptation
Split to Merge: Unifying Separated Modalities for Unsupervis...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Li, Xinyao Li, Yuke Du, Zhekai Li, Fengling Lu, Ke Li, Jingjing Univ Elect Sci & Technol China Chengdu Peoples R China Boston Coll Chestnut Hill MA 02167 USA Univ Technol Sydney Sydney NSW Australia
Large vision-language models (VLMs) like CLIP have demonstrated good zero-shot learning performance in the unsupervised domain adaptation task. Yet, most transfer approaches for VLMs focus on either the language or vi... 详细信息
来源: 评论
ieee computer society conference on computer vision and pattern recognition Workshops
IEEE Computer Society Conference on Computer Vision and Patt...
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31st Meeting of the ieee/CVF conference on computer vision and pattern recognition Workshops, CVPRW 2018
The proceedings contain 307 papers. The topics discussed include: deep features for recognizing disguised faces in the wild;unconstrained fingerphoto database;hybrid user-independent and user-dependent offline signatu...
来源: 评论
Transductive Zero-Shot and Few-Shot CLIP
Transductive Zero-Shot and Few-Shot CLIP
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Martin, Segolene Huang, Yunshi Shakeri, Fereshteh Pesquet, Jean-Christophe Ben Ayed, Ismail Univ Paris Saclay CVN Cent Supelec INRIA Paris France ETS Montreal Montreal PQ Canada
Transductive inference has been widely investigated in few-shot image classification, but completely overlooked in the recent, fast growing literature on adapting vision-langage models like CLIP. This paper addresses ... 详细信息
来源: 评论
Not All Prompts Are Secure: A Switchable Backdoor Attack Against Pre-trained vision Transfomers
Not All Prompts Are Secure: A Switchable Backdoor Attack Aga...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Yang, Sheng Bai, Jiawang Gao, Kuofeng Yang, Yong Li, Yiming Xia, Shu-Tao Tsinghua Univ Beijing Peoples R China Tencent Secur Platform Dept Shenzhen Peoples R China Zhejiang Univ Hangzhou Peoples R China Peng Cheng Lab Res Ctr Artificial Intelligence Shenzhen Peoples R China
Given the power of vision transformers, a new learning paradigm, pretraining and then prompting, makes it more efficient and effective to address downstream visual recognition tasks. In this paper, we identify a novel... 详细信息
来源: 评论
vision-language models for decoding provider attention during neonatal resuscitation
Vision-language models for decoding provider attention durin...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Parodi, Felipe Matelsky, Jordan K. Regla-Vargas, Alejandra Foglia, Elizabeth E. Lim, Charis Weinberg, Danielle Kording, Konrad P. Herrick, Heidi M. Platt, Michael L. Univ Penn Dept Neurosci Philadelphia PA 19104 USA Univ Penn Dept Bioengn Philadelphia PA 19104 USA Univ Penn Dept Sociol Philadelphia PA 19104 USA Univ Penn Dept Mkt Philadelphia PA 19104 USA Univ Penn Dept Psychol 3815 Walnut St Philadelphia PA 19104 USA Univ Penn Dept Pediat Div Neonatol Perelman Sch Med Philadelphia PA 19104 USA Childrens Hosp Philadelphia Dept Pediat Div Neonatol Philadelphia PA 19104 USA Johns Hopkins Univ Appl Phys Lab Baltimore MD 21218 USA
Neonatal resuscitations demand an exceptional level of attentiveness from providers, who must process multiple streams of information simultaneously. Gaze strongly influences decision making;thus, understanding where ... 详细信息
来源: 评论
Exploring Regional Clues in CLIP for Zero-Shot Semantic Segmentation
Exploring Regional Clues in CLIP for Zero-Shot Semantic Segm...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Zhang, Yi Guo, Meng-Hao Wang, Miao Hu, Shi-Min Beihang Univ State Key Lab Virtual Real Technol & Syst SCSE Beijing Peoples R China Tsinghua Univ Dept Comp Sci & Technol BNRist Beijing Peoples R China Tsinghua Univ Beijing Peoples R China
CLIP has demonstrated marked progress in visual recognition due to its powerful pre-training on large-scale image-text pairs. However, it still remains a critical challenge: how to transfer image-level knowledge into ... 详细信息
来源: 评论
Towards Better vision-Inspired vision-Language Models
Towards Better Vision-Inspired Vision-Language Models
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Cao, Yun-Hao Ji, Kaixiang Huang, Ziyuan Zheng, Chuanyang Liu, Jiajia Wang, Jian Chen, Jingdong Yang, Ming Nanjing Univ Natl Key Lab Novel Software Technol Nanjing Jiangsu Peoples R China Ant Grp Hangzhou Zhejiang Peoples R China
vision-language (VL) models have achieved unprecedented success recently, in which the connection module is the key to bridge the modality gap. Nevertheless, the abundant visual clues are not sufficiently exploited in... 详细信息
来源: 评论
PeVL: Pose-Enhanced vision-Language Model for Fine-Grained Human Action recognition
PeVL: Pose-Enhanced Vision-Language Model for Fine-Grained H...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Zhang, Haosong Leong, Mei Chee Li, Liyuan Lin, Weisi Nanyang Technol Univ Inst Infocomm Res I2R A STAR Singapore Singapore
Recent progress in vision-Language (VL) foundation models has revealed the great advantages of cross-modality learning. However, due to a large gap between vision and text, they might not be able to sufficiently utili... 详细信息
来源: 评论