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检索条件"任意字段=IEEE Conference on Computer Vision and Pattern Recognition Workshops"
23198 条 记 录,以下是271-280 订阅
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UnScene3D: Unsupervised 3D Instance Segmentation for Indoor Scenes
UnScene3D: Unsupervised 3D Instance Segmentation for Indoor ...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Rozenberszki, David Litany, Or Dai, Angela Tech Univ Munich Munich Germany Technion Haifa Israel NVIDIA Santa Clara CA USA
3D instance segmentation is fundamental to geometric understanding of the world around us. Existing methods for instance segmentation of 3D scenes rely on supervision from expensive, manual 3D annotations. We propose ... 详细信息
来源: 评论
PairDETR : Joint Detection and Association of Human Bodies and Faces
PairDETR : Joint Detection and Association of Human Bodies a...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Ali, Ammar Gaikov, Georgii Rybalchenko, Denis Chigorin, Alexander Laptev, Ivan Zagoruyko, Sergey MTS AI ITMO Moscow Russia MTS AI Moscow Russia VisionLabs Hyderabad Telangana India MBZUAI Abu Dhabi U Arab Emirates MTS AI Skoltech Moscow Russia
Image and video analysis requires not only accurate object detection but also the understanding of relationships among detected objects. Common solutions to relation modeling typically resort to stand-alone object det... 详细信息
来源: 评论
Domain Prompt Learning with Quaternion Networks
Domain Prompt Learning with Quaternion Networks
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Cao, Qinglong Xu, Zhengqin Chen, Yuntian Ma, Chao Yang, Xiaokang Shanghai Jiao Tong Univ AI Inst MoE Key Lab Artificial Intelligence Shanghai Peoples R China Eastern Inst Technol Ningbo Inst Digital Twin Ningbo Peoples R China
Prompt learning has emerged as a potent and resource-efficient technique in large vision-Language Models (VLMs). However, its application in adapting VLMs to specialized domains like remote sensing and medical imaging... 详细信息
来源: 评论
WALT3D: Generating Realistic Training Data from Time-Lapse Imagery for Reconstructing Dynamic Objects under Occlusion
WALT3D: Generating Realistic Training Data from Time-Lapse I...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Khiem Vuong Reddy, N. Dinesh Tamburo, Robert Narasimhan, Srinivasa G. Carnegie Mellon Univ Pittsburgh PA 15213 USA Amazon Seattle WA USA
Current methods for 2D and 3D object understanding struggle with severe occlusions in busy urban environments, partly due to the lack of large-scale labeled groundtruth annotations for learning occlusion. In this work... 详细信息
来源: 评论
Any-Shift Prompting for Generalization over Distributions
Any-Shift Prompting for Generalization over Distributions
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Xiao, Zehao Shen, Jiayi Derakhshani, Mohammad Mandi Liao, Shengcai Snoek, Cees G. M. Univ Amsterdam Amsterdam Netherlands Core42 Abu Dhabi U Arab Emirates
Image-language models with prompt learning have shown remarkable advances in numerous downstream vision tasks. Nevertheless, conventional prompt learning methods overfit their training distribution and lose the genera... 详细信息
来源: 评论
Perturbing Attention Gives You More Bang for the Buck: Subtle Imaging Perturbations That Efficiently Fool Customized Diffusion Models
Perturbing Attention Gives You More Bang for the Buck: Subtl...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Xu, Jingyao Lu, Yuetong Li, Yandong Lu, Siyang Wang, Dongdong Wei, Xiang Beijing Jiaotong Univ Beijing Peoples R China Google Res Mountain View CA USA Univ Cent Florida Orlando FL 32816 USA
Diffusion models ( DMs) embark a new era of generative modeling and offer more opportunities for efficient generating high- quality and realistic data samples. However, their widespread use has also brought forth new ... 详细信息
来源: 评论
Instance-Aware Group Quantization for vision Transformers
Instance-Aware Group Quantization for Vision Transformers
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Jaehyeon, Moon Kim, Dohyung Cheon, Junyong Ham, Bumsub Yonsei Univ Seoul South Korea Articron Bogota Colombia
Post-training quantization (PTQ) is an efficient model compression technique that quantizes a pretrained full-precision model using only a small calibration set of unlabeled samples without retraining. PTQ methods for... 详细信息
来源: 评论
Learning to Predict Activity Progress by Self-Supervised Video Alignment
Learning to Predict Activity Progress by Self-Supervised Vid...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Donahue, Gerard Elhamifar, Ehsan Northwestern Univ Boston MA 02115 USA
In this paper, we tackle the problem of self-supervised video alignment and activity progress prediction using in-the-wild videos. Our proposed self-supervised representation learning method carefully addresses differ... 详细信息
来源: 评论
SonicvisionLM: Playing Sound with vision Language Models
SonicVisionLM: Playing Sound with Vision Language Models
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Xie, Zhifeng Yu, Shengye He, Qile Li, Mengtian Shanghai Univ Shanghai Peoples R China Shanghai Engn Res Ctr Mot Picture Special Effects Shanghai Peoples R China
There has been a growing interest in the task of generating sound for silent videos, primarily because of its practicality in streamlining video post-production. However, existing methods for video-sound generation at... 详细信息
来源: 评论
Masked AutoDecoder is Effective Multi-Task vision Generalist
Masked AutoDecoder is Effective Multi-Task Vision Generalist
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Qiu, Han Huang, Jiaxing Gao, Peng Lu, Lewei Zhang, Xiaoqin Lu, Shijian Nanyang Technol Univ S Lab Singapore Singapore Shanghai Artificial Intelligence Lab Shanghai Peoples R China Sensetime Res Beijing Peoples R China Zhejiang Univ Technol Coll Comp Sci & Technol Hangzhou Peoples R China
Inspired by the success of general-purpose models in NLP, recent studies attempt to unify different vision tasks in the same sequence format and employ autoregressive Transformers for sequence prediction. They apply u... 详细信息
来源: 评论