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检索条件"任意字段=1994 IEEE Computer-Society Conference on Computer Vision and Pattern Recognition"
22907 条 记 录,以下是4641-4650 订阅
排序:
Fully Understanding Generic Objects: Modeling, Segmentation, and Reconstruction
Fully Understanding Generic Objects: Modeling, Segmentation,...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Liu, Feng Tran, Luan Liu, Xiaoming Michigan State Univ E Lansing MI 48824 USA
Inferring 3D structure of a generic object from a 2D image is a long-standing objective of computer vision. Conventional approaches either learn completely from CAD-generated synthetic data, which have difficulty in i... 详细信息
来源: 评论
Learnable Global Spatio-Temporal Adaptive Aggregation for Bracketing Image Restoration and Enhancement
Learnable Global Spatio-Temporal Adaptive Aggregation for Br...
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ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)
作者: Xinwei Dai Yuanbo Zhou Xintao Qiu Hui Tang Wei Deng Qingquan Gao Tong Tong Fuzhou University Imperial Vision Technology
Employing specific networks to address different types of degradation often proved to be complex and time-consuming in practical applications. The Bracket Image Restoration and Enhancement (BIRE) aimed to address vari... 详细信息
来源: 评论
Meta Batch-Instance Normalization for Generalizable Person Re-Identification
Meta Batch-Instance Normalization for Generalizable Person R...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Choi, Seokeon Kim, Taekyung Jeong, Minki Park, Hyoungseob Kim, Changick Korea Adv Inst Sci & Technol Daejeon South Korea
Although supervised person re-identification (Re-ID) methods have shown impressive performance, they suffer from a poor generalization capability on unseen domains. Therefore, generalizable Re-ID has recently attracte... 详细信息
来源: 评论
Prompting Foundational Models for Omni-supervised Instance Segmentation
Prompting Foundational Models for Omni-supervised Instance S...
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ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)
作者: Arnav M. Das Ritwick Chaudhry Kaustav Kundu Davide Modolo University of Washington Seattle AWS AI Labs
Pixel-level mask annotation costs are a major bottleneck in training deep neural networks for instance segmentation. Recent promptable foundation models like the Segment Anything Model (SAM) and GroundedDINO (GDino) h... 详细信息
来源: 评论
Unsupervised Domain Adaptation for Weed Segmentation Using Greedy Pseudo-labelling
Unsupervised Domain Adaptation for Weed Segmentation Using G...
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ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)
作者: Yingchao Huang Abdul Bais University of Regina Regina Canada
Automatic weed identification based on RGB images with convolutional neural networks (CNN) is a new frontier of precision agriculture. However, the CNN models expect a large volume of labelled data. Their performance ... 详细信息
来源: 评论
MonoSelfRecon: Purely Self-Supervised Explicit Generalizable 3D Reconstruction of Indoor Scenes from Monocular RGB Views
MonoSelfRecon: Purely Self-Supervised Explicit Generalizable...
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ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)
作者: Runfa Li Upal Mahbub Vasudev Bhaskaran Truong Nguyen UC San Diego Qualcomm
Current monocular 3D scene reconstruction (3DR) works are either fully-supervised, or not generalizable, or implicit in 3D representation. We propose a novel framework - MonoSelfRecon that for the first time achieves ... 详细信息
来源: 评论
Learning by Watching
Learning by Watching
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Zhang, Jimuyang Ohn-Bar, Eshed Boston Univ Boston MA 02215 USA
When in a new situation or geographical location, human drivers have an extraordinary ability to watch others and learn maneuvers that they themselves may have never performed. In contrast, existing techniques for lea... 详细信息
来源: 评论
AdCo: Adversarial Contrast for Efficient Learning of Unsupervised Representations from Self-Trained Negative Adversaries
AdCo: Adversarial Contrast for Efficient Learning of Unsuper...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Hu, Qianjiang Wang, Xiao Hu, Wei Qi, Guo-Jun Peking Univ Beijing Peoples R China Purdue Univ W Lafayette IN 47907 USA Lab MAchine Percept & LEarning MAPLE Beijing Peoples R China
Contrastive learning relies on constructing a collection of negative examples that are sufficiently hard to discriminate against positive queries when their representations are self-trained. Existing contrastive learn... 详细信息
来源: 评论
Improving Object Detection to Fisheye Cameras with Open-Vocabulary Pseudo-Label Approach
Improving Object Detection to Fisheye Cameras with Open-Voca...
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ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)
作者: Long Hoang Pham Quoc Pham-Nam Ho Duong Nguyen-Ngoc Tran Tai Huu-Phuong Tran Huy-Hung Nguyen Duong Khac Vu Chi Dai Tran Ngoc Doan-Minh Huynh Hyung-Min Jeon Hyung-Joon Jeon Jae Wook Jeon Department of Electrical and Computer Engineering Sungkyunkwan University
Fish-eye cameras have long been employed in traffic surveillance systems to allow for wider observation of the roads. Despite their widespread use, limited computer vision research is tailored explicitly to images cap... 详细信息
来源: 评论
Learning Tracking Representations from Single Point Annotations
Learning Tracking Representations from Single Point Annotati...
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ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)
作者: Qiangqiang Wu Antoni B. Chan Department of Computer Science City University of Hong Kong
Existing deep trackers are typically trained with large-scale video frames with annotated bounding boxes. However, these bounding boxes are expensive and time-consuming to annotate, in particular for large scale datas... 详细信息
来源: 评论