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检索条件"任意字段=2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011"
21099 条 记 录,以下是121-130 订阅
排序:
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
Efficient Test-Time Adaptation of vision-Language Models
Efficient Test-Time Adaptation of Vision-Language Models
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Karmanov, Adilbek Guan, Dayan Lu, Shijian El Saddik, Abdulmotaleb Xing, Eric Mohamed bin Zayed Univ Artificial Intelligence Abu Dhabi U Arab Emirates Nanyang Technol Univ Singapore Singapore Univ Ottawa Ottawa ON Canada Carnegie Mellon Univ Pittsburgh PA 15213 USA
Test-time adaptation with pre-trained vision-language models has attracted increasing attention for tackling distribution shifts during the test time. Though prior studies have achieved very promising performance, the...
来源: 评论
Projecting Trackable Thermal patterns for Dynamic computer vision
Projecting Trackable Thermal Patterns for Dynamic Computer V...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Sheinin, Mark Sankaranarayanan, Aswin C. Narasimhan, Srinivasa G. Carnegie Mellon Univ Pittsburgh PA 15213 USA
Adding artificial patterns to objects, like QR codes, can ease tasks such as object tracking, robot navigation, and conveying information (e.g., a label or a website link). However, these patterns require a physical a... 详细信息
来源: 评论
SocialCounterfactuals: Probing and Mitigating Intersectional Social Biases in vision-Language Models with Counterfactual Examples
SocialCounterfactuals: Probing and Mitigating Intersectional...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Howard, Phillip Madasu, Avinash Le, Tiep Moreno, Gustavo Lujan Bhiwandiwalla, Anahita Lal, Vasudev Intel Labs Santa Clara CA 95052 USA
While vision-language models (VLMs) have achieved remarkable performance improvements recently, there is growing evidence that these models also posses harmful biases with respect to social attributes such as gender a... 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
OOSTraj: Out-of-Sight Trajectory Prediction With vision-Positioning Denoising
OOSTraj: Out-of-Sight Trajectory Prediction With Vision-Posi...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Zhang, Haichao Xu, Yi Lu, Hongsheng Shimizu, Takayuki Fu, Yun Northeastern Univ 360 Huntington Ave Boston MA 02115 USA Toyota Motor North Amer 465 N Bernardo Ave Mountain View CA 94043 USA
Trajectory prediction is fundamental in computer vision and autonomous driving, particularly for understanding pedestrian behavior and enabling proactive decision-making. Existing approaches in this field often assume... 详细信息
来源: 评论
RegionGPT: Towards Region Understanding vision Language Model
RegionGPT: Towards Region Understanding Vision Language Mode...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Guo, Qiushan De Mello, Shalini Yin, Hongxu Byeon, Wonmin Cheung, Ka Chun Yu, Yizhou Luo, Ping Liu, Sifei Univ Hong Kong Hong Kong Peoples R China NVIDIA San Francisco CA USA
vision language models (VLMs) have experienced rapid advancements through the integration of large language models (LLMs) with image-text pairs, yet they struggle with detailed regional visual understanding due to lim...
来源: 评论
BIOCLIP: A vision Foundation Model for the Tree of Life
BIOCLIP: A Vision Foundation Model for the Tree of Life
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Stevens, Samuel Wu, Jiaman Thompson, Matthew J. Campolongo, Elizabeth G. Song, Chan Hee Carlyle, David Edward Dong, Li Dahdul, Wasila M. Stewart, Charles Berger-Wolf, Tanya Chao, Wei-Lun Su, Yu Ohio State Univ Columbus OH 43210 USA Microsoft Res Mountain View CA USA Univ Calif Irvine Irvine CA USA Rensselaer Polytech Inst Troy NY USA
Images of the natural world, collected by a variety of cameras, from drones to individual phones, are increasingly abundant sources of biological information. There is an explosion of computational methods and tools, ... 详细信息
来源: 评论
Generative Rendering: Controllable 4D-Guided Video Generation with 2D Diffusion Models
Generative Rendering: Controllable 4D-Guided Video Generatio...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Cai, Shengqu Ceylan, Duygu Gadelha, Matheus Huang, Chun-Hao Paul Wang, Tuanfeng Yang Wetzstein, Gordon Stanford Univ Stanford CA 94305 USA Adobe Res San Francisco CA USA
Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos... 详细信息
来源: 评论
Transcending the Limit of Local Window: Advanced Super-Resolution Transformer with Adaptive Token Dictionary
Transcending the Limit of Local Window: Advanced Super-Resol...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Zhang, Leheng Li, Yawei Zhou, Xingyu Zhao, Xiaorui Gu, Shuhang Univ Elect Sci & Technol China Chengdu Peoples R China Swiss Fed Inst Technol Comp Vis Lab Zurich Switzerland Swiss Fed Inst Technol Integrated Syst Lab Zurich Switzerland
Single Image Super-Resolution is a classic computer vision problem that involves estimating high-resolution (HR) images from low-resolution (LR) ones. Although deep neural networks (DNNs), especially Transformers for ... 详细信息
来源: 评论