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检索条件"任意字段=IEEE-Computer-Society Conference on Computer Vision and Pattern Recognition Workshops"
8947 条 记 录,以下是301-310 订阅
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Online Unsupervised Domain Adaptation for Person Re-identification
Online Unsupervised Domain Adaptation for Person Re-identifi...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Rami, Hamza Ospici, Matthieu Lathuiliere, Stephane Inst Polytech Paris Telecom Paris LTCI Paris France Atos London England
Unsupervised domain adaptation for person re-identification (Person Re-ID) is the task of transferring the learned knowledge on the labeled source domain to the unlabeled target domain. Most of the recent papers that ... 详细信息
来源: 评论
Linear Combination Approximation of Feature for Channel Pruning
Linear Combination Approximation of Feature for Channel Prun...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Joo, Donggyu Kim, Doyeon Yi, Eojindl Kim, Junmo Korea Adv Inst Sci & Technol KAIST Daejeon South Korea
Network pruning is an effective method that reduces the computation of neural networks while maintaining high performance. This enables the operation of deep neural networks in resource-limited environments. In a gene... 详细信息
来源: 评论
Momentum Contrastive Pruning
Momentum Contrastive Pruning
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Pan, Siyuan Qin, Yiming Li, Tingyao Li, Xiaoshuang Hou, Liang Shanghai Jiao Tong Univ Shanghai Peoples R China Chinese Acad Sci Inst Comp Technol Beijing Peoples R China
Momentum contrast [16] (MoCo) for unsupervised visual representation learning has a close performance to supervised learning, but it sometimes possesses excess parameters. Extracting a subnetwork from an over-paramete... 详细信息
来源: 评论
Video Action Detection: Analysing Limitations and Challenges
Video Action Detection: Analysing Limitations and Challenges
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Modi, Rajat Rana, Aayush Jung Kumar, Akash Tirupattur, Praveen Vyas, Shruti Rawat, Yogesh Singh Shah, Mubarak Univ Cent Florida Ctr Res Comp Vis Orlando FL 32816 USA
Beyond possessing large enough size to feed data hungry machines (eg, transformers), what attributes measure the quality of a dataset? Assuming that the definitions of such attributes do exist, how do we quantify amon... 详细信息
来源: 评论
Dress Code: High-Resolution Multi-Category Virtual Try-On
Dress Code: High-Resolution Multi-Category Virtual Try-On
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Morelli, Davide Fincato, Matteo Cornia, Marcella Landi, Federico Cesari, Fabio Cucchiara, Rita Univ Modena & Reggio Emilia Modena Italy YOOX NET A PORTER GRP Milan Italy
Image-based virtual try-on strives to transfer the appearance of a clothing item onto the image of a target person. Existing literature focuses mainly on upper-body clothes (e.g. t-shirts, shirts, and tops) and neglec... 详细信息
来源: 评论
Is Multimodal vision Supervision Beneficial to Language?
Is Multimodal Vision Supervision Beneficial to Language?
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2023 ieee/CVF conference on computer vision and pattern recognition workshops, CVPRW 2023
作者: Madasu, Avinash Lal, Vasudev Unc Chapel Hill Department of Computer Science United States Cognitive Computing Research Intel Labs United States
vision (image & video) - Language (VL) pre-training is the recent popular paradigm that achieved state-of-the-art results on multi-modal tasks like image-retrieval, video-retrieval, visual question answering etc. ... 详细信息
来源: 评论
Unsupervised Anomaly Detection from Time-of-Flight Depth Images
Unsupervised Anomaly Detection from Time-of-Flight Depth Ima...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Schneider, Pascal Rambach, Jason Mirbach, Bruno Stricker, Didier German Res Ctr Artificial Intelligence DFKI Trippstadter Str 122 D-67663 Kaiserslautern Germany
Video anomaly detection (VAD) addresses the problem of automatically finding anomalous events in video data. The primary data modalities on which current VAD systems work on are monochrome or RGB images. Using depth d... 详细信息
来源: 评论
PseudoProp: Robust Pseudo-Label Generation for Semi-Supervised Object Detection in Autonomous Driving Systems
PseudoProp: Robust Pseudo-Label Generation for Semi-Supervis...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Hu, Shu Liu, Chun-Hao Dutta, Jayanta Chang, Ming-Ching Lyu, Siwei Ramakrishnan, Naveen Univ Buffalo SUNY Buffalo NY USA Bosch Ctr Artificial Intelligence Sunnyvale CA 94085 USA SUNY Albany Albany NY 12222 USA Amazon Seattle WA USA
Semi-supervised object detection methods are widely used in autonomous driving systems, where only a fraction of objects are labeled. To propagate information from the labeled objects to the unlabeled ones, pseudo-lab... 详细信息
来源: 评论
Ex-Model: Continual Learning from a Stream of Trained Models
Ex-Model: Continual Learning from a Stream of Trained Models
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Carta, Antonio Cossu, Andrea Lomonaco, Vincenzo Bacciu, Davide Univ Pisa Pisa Italy Scuola Normale Super Pisa Pisa Italy
Learning continually from non-stationary data streams is a challenging research topic of growing popularity in the last few years. Being able to learn, adapt, and generalize continually in an efficient, effective, and... 详细信息
来源: 评论
Towards a Deeper Understanding of Skeleton-based Gait recognition
Towards a Deeper Understanding of Skeleton-based Gait Recogn...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Teepe, Torben Gilg, Johannes Herzog, Fabian Hoermann, Stefan Rigoll, Gerhard Tech Univ Munich Munich Germany
Gait recognition is a promising biometric with unique properties for identifying individuals from a long distance by their walking patterns. In recent years, most gait recognition methods used the person's silhoue... 详细信息
来源: 评论