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检索条件"任意字段=2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011"
21179 条 记 录,以下是101-110 订阅
排序:
Resource-Efficient Transformer Pruning for Finetuning of Large Models
Resource-Efficient Transformer Pruning for Finetuning of Lar...
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Ilhan, Fatih Su, Gong Tekin, Selim Furkan Huang, Tiansheng Hu, Sihao Liu, Ling Georgia Inst Technol Atlanta GA 30332 USA IBM Res Yorktown Hts NY USA
With the recent advances in vision transformers and large language models (LLMs), finetuning costly large models on downstream learning tasks poses significant challenges under limited computational resources. This pa... 详细信息
来源: 评论
Neural Refinement for Absolute Pose Regression with Feature Synthesis
Neural Refinement for Absolute Pose Regression with Feature ...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Chen, Shuai Bhalgat, Yash Li, Xinghui Bin, Jia-Wang Li, Kejie Wang, Zirui Prisacariu, Victor Adrian Univ Oxford Act Vision Lab Oxford England Univ Oxford Visual Geometry Grp Oxford England
Absolute Pose Regression (APR) methods use deep neural networks to directly regress camera poses from RGB images. However, the predominant APR architectures only rely on 2D operations during inference, resulting in li... 详细信息
来源: 评论
Intrinsic Image Diffusion for Indoor Single-view Material Estimation
Intrinsic Image Diffusion for Indoor Single-view Material Es...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Kocsis, Peter Sitzmann, Vincent Niessner, Matthias Tech Univ Munich Munich Germany MIT EECS Cambridge MA 02139 USA
We present Intrinsic Image Diffusion, a generative model for appearance decomposition of indoor scenes. Given a single input view, we sample multiple possible material explanations represented as albedo, roughness, an... 详细信息
来源: 评论
Physical Property Understanding from Language-Embedded Feature Fields
Physical Property Understanding from Language-Embedded Featu...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Zhai, Albert J. Shen, Yuan Chen, Emily Y. Wang, Gloria X. Wang, Xinlei Wang, Sheng Guan, Kaiyu Wang, Shenlong Univ Illinois Champaign IL 61820 USA
Can computers perceive the physical properties of objects solely through vision? Research in cognitive science and vision science has shown that humans excel at identifying materials and estimating their physical prop... 详细信息
来源: 评论
Learning by Correction: Efficient Tuning Task for Zero-Shot Generative vision-Language Reasoning
Learning by Correction: Efficient Tuning Task for Zero-Shot ...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Li, Rongjie Wu, Yu He, Xuming ShanghaiTech Univ Sch Informat Sci & Technol Shanghai Peoples R China Shanghai Engn Res Ctr Intelligent Vis & Imaging Shanghai Peoples R China
Generative vision-language models (VLMs) have shown impressive performance in zero-shot vision-language tasks like image captioning and visual question answering. However, improving their zero-shot reasoning typically... 详细信息
来源: 评论
VicTR: Video-conditioned Text Representations for Activity recognition
VicTR: Video-conditioned Text Representations for Activity R...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Kahatapitiya, Kumara Arnab, Anurag Nagrani, Arsha Ryoo, Michael S. SUNY Stony Brook Stony Brook NY 11794 USA Google Res Mountain View CA USA
vision-Language models (VLMs) have excelled in the image-domain- especially in zero-shot settings- thanks to the availability of vast pretraining data (i.e., paired image-text samples). However for videos, such paired... 详细信息
来源: 评论
Bi-Causal: Group Activity recognition via Bidirectional Causality
Bi-Causal: Group Activity Recognition via Bidirectional Caus...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Zhang, Youliang Liu, Wenxuan Xu, Danni Zhou, Zhuo Wang, Zheng Wuhan Univ Natl Engn Res Ctr Multimedia Software Sch Comp Sci Inst Artificial Intelligence Wuhan Hubei Peoples R China Hubei Key Lab Multimedia & Network Commun Engn Wuhan Hubei Peoples R China Wuhan Univ Technol Wuhan Hubei Peoples R China Natl Univ Singapore Singapore Singapore
Current approaches in Group Activity recognition (GAR) predominantly emphasize Human Relations (HRs) while often neglecting the impact of Human-Object Interactions (HOIs). This study prioritizes the consideration of b... 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
Probing the 3D Awareness of Visual Foundation Models
Probing the 3D Awareness of Visual Foundation Models
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: El Banani, Mohamed Raj, Amit Maninis, Kevis-Kokitsi Kar, Abhishek Li, Yuanzhen Rubinstein, Michael Sun, Deqing Guibas, Leonidas Johnson, Justin Jampani, Varun Univ Michigan Ann Arbor MI 48109 USA Google Mountain View CA 94043 USA Stability AI London ON Canada
Recent advances in large-scale pretraining have yielded visual foundation models with strong capabilities. Not only can recent models generalize to arbitrary images for their training task, their intermediate represen... 详细信息
来源: 评论
Eclipse: Disambiguating Illumination and Materials using Unintended Shadows
Eclipse: Disambiguating Illumination and Materials using Uni...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Verbin, Dor Mildenhall, Ben Hedman, Peter Barron, Jonathan T. Zickler, Todd Srinivasan, Pratul P. Google Res Mountain View CA 94043 USA Harvard Univ Cambridge MA USA
Decomposing an object's appearance into representations of its materials and the surrounding illumination is difficult, even when the object's 3D shape is known beforehand. This problem is especially challengi... 详细信息
来源: 评论