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检索条件"任意字段=IEEE Conference on Computer Vision and Pattern Recognition Workshops"
23095 条 记 录,以下是241-250 订阅
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On the Faithfulness of vision Transformer Explanations
On the Faithfulness of Vision Transformer Explanations
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Wu, Junyi Kang, Weitai Tang, Hao Hong, Yuan Yan, Yan IIT Dept Comp Sci Chicago IL 60616 USA Carnegie Mellon Univ Robot Inst Pittsburgh PA 15213 USA Univ Connecticut Dept Comp Sci Storrs CT USA
To interpret vision Transformers, post-hoc explanations assign salience scores to input pixels, providing human-understandable heatmaps. However, whether these interpretations reflect true rationales behind the model&... 详细信息
来源: 评论
A Backpack Full of Skills: Egocentric Video Understanding with Diverse Task Perspectives
A Backpack Full of Skills: Egocentric Video Understanding wi...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Peirone, Simone Alberto Pistilli, Francesca Alliegro, Antonio Averta, Giuseppe Politecnico Torino Turin Italy Ist Italiano Tecnol Genoa Italy
Human comprehension of a video stream is naturally broad: in a few instants, we are able to understand what is happening, the relevance and relationship of objects, and forecast what will follow in the near future, ev... 详细信息
来源: 评论
On the Robustness of Language Guidance for Low-Level vision Tasks: Findings from Depth Estimation
On the Robustness of Language Guidance for Low-Level Vision ...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Chatterjee, Agneet Gokhale, Tejas Baral, Chitta Yang, Yezhou Arizona State Univ Tempe AZ 85281 USA Univ Maryland Baltimore Cty Baltimore MD 21228 USA
Recent advances in monocular depth estimation have been made by incorporating natural language as additional guidance. Although yielding impressive results, the impact of the language prior, particularly in terms of g... 详细信息
来源: 评论
H-ViT: A Hierarchical vision Transformer for Deformable Image Registration
H-ViT: A Hierarchical Vision Transformer for Deformable Imag...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Ghahremani, Morteza Khateri, Mohammad Jian, Bailiang Wiestler, Benedikt Adeli, Ehsan Wachinger, Christian Tech Univ Munich Munich Germany Munich Ctr Machine Learning Munich Germany Univ Eastern Finland Espoo Finland Stanford Univ Stanford CA 94305 USA
This paper introduces a novel top-down representation approach for deformable image registration, which estimates the deformation field by capturing various short-and long-range flow features at different scale levels... 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
Proceedings - 2024 ieee Winter conference on Applications of computer vision workshops, WACVW 2024
Proceedings - 2024 IEEE Winter Conference on Applications of...
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2024 ieee/CVF Winter conference on Applications of computer vision workshops, WACVW 2024
The proceedings contain 123 papers. The topics discussed include: the SARFish dataset and challenge;NORPPA: NOvel ringed seal re-identification by pelage pattern aggregation;multiple toddler tracking in indoor videos;...
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
Action Scene Graphs for Long-Form Understanding of Egocentric Videos
Action Scene Graphs for Long-Form Understanding of Egocentri...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Rodin, Ivan Furnari, Antonino Min, Kyle Tripathi, Subarna Farinella, Giovanni Maria Univ Catania Catania Italy Intel Labs Hillsboro OR USA
We present Egocentric Action Scene Graphs (EASGs), a new representation for long-form understanding of egocentric videos. EASGs extend standard manually-annotated representations of egocentric videos, such as verb-nou... 详细信息
来源: 评论
Context-based and Diversity-driven Specificity in Compositional Zero-Shot Learning
Context-based and Diversity-driven Specificity in Compositio...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Li, Yun Liu, Zhe Chen, Hang Yao, Lina CSIROs Data61 Clayton Vic Australia Bytedance Ltd Beijing Peoples R China Snap Inc Santa Monica CA USA
Compositional Zero-Shot Learning (CZSL) aims to recognize unseen attribute-object pairs based on a limited set of observed examples. Current CZSL methodologies, despite their advancements, tend to neglect the distinct... 详细信息
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