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检索条件"任意字段=2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2024"
4655 条 记 录,以下是341-350 订阅
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Test-Time Adaptation for Depth Completion
Test-Time Adaptation for Depth Completion
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Park, Hyoungseob Gupta, Anjali Wong, Alex Yale Vision Lab New Haven CT 06501 USA
It is common to observe performance degradation when transferring models trained on some (source) datasets to target testing data due to a domain gap between them. Existing methods for bridging this gap, such as domai... 详细信息
来源: 评论
On the test-time zero-shot generalization of vision-language models: Do we really need prompt learning?
On the test-time zero-shot generalization of vision-language...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Zanella, Maxime Ben Ayed, Ismail UCLouvain Louvain Belgium UMons Mons Belgium ETS Montreal Montreal PQ Canada
The development of large vision-language models, notably CLIP, has catalyzed research into effective adaptation techniques, with a particular focus on soft prompt tuning. Conjointly, test-time augmentation, which util... 详细信息
来源: 评论
THRONE: An Object-based Hallucination Benchmark for the Free-form Generations of Large vision-Language Models
THRONE: An Object-based Hallucination Benchmark for the Free...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Kaul, Prannay Li, Zhizhong Yang, Hao Dukler, Yonatan Swaminathan, Ashwin Taylor, C. J. Soatto, Stefano Univ Oxford VGG Oxford England AWS AI Labs Oxford England
Mitigating hallucinations in large vision-language models (LVLMs) remains an open problem. Recent benchmarks do not address hallucinations in open-ended free-form responses, which we term "Type I hallucinations&q... 详细信息
来源: 评论
Sharingan: A Transformer Architecture for Multi-Person Gaze Following
Sharingan: A Transformer Architecture for Multi-Person Gaze ...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Tafasca, Samy Gupta, Anshul Odobez, Jean-Marc Idiap Res Inst Martigny Switzerland Ecole Polytech Fed Lausanne Lausanne Switzerland
Gaze is a powerful form of non-verbal communication that humans develop from an early age. As such, modeling this behavior is an important task that can benefit a broad set of application domains ranging from robotics... 详细信息
来源: 评论
Distilling vision-Language Models on Millions of Videos
Distilling Vision-Language Models on Millions of Videos
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Zhao, Yue Zhao, Long Zhou, Xingyi Wu, Jialin Chu, Chun-Te Mia, Hui Schroff, Florian Adam, Hartwig Liu, Ting Gong, Boqing Krahenbuhl, Philipp Yuan, Liangzhe Google Res Mountain View CA 94043 USA Univ Texas Austin Austin TX 78712 USA
The recent advance in vision-language models is largely attributed to the abundance of image-text data. We aim to replicate this success for video-language models, but there simply is not enough human- curated video-t... 详细信息
来源: 评论
3D Human Pose Perception from Egocentric Stereo Videos
3D Human Pose Perception from Egocentric Stereo Videos
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Akada, Hiroyasu Wang, Jian Golyanik, Vladislav Theobalt, Christian Max Planck Inst Informat SIC Saarbrucken Germany
While head-mounted devices are becoming more compact, they provide egocentric views with significant self-occlusions of the device user. Hence, existing methods often fail to accurately estimate complex 3D poses from ... 详细信息
来源: 评论
Synthesize, Diagnose, and Optimize: Towards Fine-Grained vision-Language Understanding
Synthesize, Diagnose, and Optimize: Towards Fine-Grained Vis...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Peng, Wujian Xi, Sicheng You, Zuyao Lan, Shiyi Wu, Zuxuan Fudan Univ Sch CS Shanghai Key Lab Intell Info Proc Shanghai Peoples R China Shanghai Collaborat Innovat Ctr Intelligent Visua Shanghai Peoples R China NVIDIA Shenzhen Guangdong Peoples R China
vision language models (VLM) have demonstrated remarkable performance across various downstream tasks. However, understanding fine-grained visual-linguistic concepts, such as attributes and inter-object relationships,... 详细信息
来源: 评论
SpatialVLM: Endowing vision-Language Models with Spatial Reasoning Capabilities
SpatialVLM: Endowing Vision-Language Models with Spatial Rea...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Chen, Boyuan Xu, Zhuo Kirman, Sean Ichter, Brian Sadigh, Dorsa Guibas, Leonidas Xia, Fei Google DeepMind London England Google Res Mountain View CA USA MIT 77 Massachusetts Ave Cambridge MA 02139 USA
Understanding and reasoning about spatial relationships is a fundamental capability for Visual Question Answering (VQA) and robotics. While vision Language Models (VLM) have demonstrated remarkable performance in cert... 详细信息
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ViP-LLaVA: Making Large Multimodal Models Understand Arbitrary Visual Prompts
ViP-LLaVA: Making Large Multimodal Models Understand Arbitra...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Cai, Mu Liu, Haotian Mustikovela, Siva Karthik Meyer, Gregory P. Chai, Yuning Park, Dennis Lee, Yong Jae Univ Wisconsin Madison WI 53706 USA Cruise LLC San Francisco CA USA
While existing large vision-language multimodal models focus on whole image understanding, there is a prominent gap in achieving region-specific comprehension. Current approaches that use textual coordinates or spatia... 详细信息
来源: 评论
Forecasting of 3D Whole-body Human Poses with Grasping Objects
Forecasting of 3D Whole-body Human Poses with Grasping Objec...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Yan, Haitao Cui, Qiongjie Xie, Jiexin Guo, Shijie Fudan Univ Acad Engn & Technol Shanghai Peoples R China Nanjing Univ Sci & Technol Nanjing Peoples R China
In the context of computer vision and human-robot interaction, forecasting 3D human poses is crucial for understanding human behavior and enhancing the predictive capabilities of intelligent systems. While existing me... 详细信息
来源: 评论