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检索条件"任意字段=2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023"
3320 条 记 录,以下是231-240 订阅
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Localized Triplet Loss for Fine-grained Fashion Image Retrieval
Localized Triplet Loss for Fine-grained Fashion Image Retrie...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: D'Innocente, Antonio Garg, Nikhil Zhang, Yuan Bazzani, Loris Donoser, Michael Sapienza Univ Rome Rome Italy Amazon Munich Germany Amazon Seattle WA USA
Fashion retrieval methods aim at learning a clothing-specific embedding space where images are ranked based on their global visual similarity with a given query. However, global embeddings struggle to capture localize... 详细信息
来源: 评论
LoL-V2T: Large-Scale Esports Video Description Dataset
LoL-V2T: Large-Scale Esports Video Description Dataset
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Tanaka, Tsunehiko Simo-Serra, Edgar Waseda Univ Tokyo Japan
Esports is a fastest-growing new field with a largely online-presence, and is creating a demand for automatic domain-specific captioning tools. However, at the current time, there are few approaches that tackle the es... 详细信息
来源: 评论
Any-Width Networks
Any-Width Networks
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Vu, Thanh Eder, Marc Price, True Frahm, Jan-Michael Univ North Carolina Chapel Hill NC 27515 USA
Despite remarkable improvements in speed and accuracy, convolutional neural networks (CNNs) still typically operate as monolithic entities at inference time. This poses a challenge for resource-constrained practical a... 详细信息
来源: 评论
Motion Fused Frames: Data Level Fusion Strategy for Hand Gesture recognition  31
Motion Fused Frames: Data Level Fusion Strategy for Hand Ges...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Kopuklu, Okan Kose, Neslihan Rigoll, Gerhard Tech Univ Munich Inst Human Machine Commun Munich Germany
Acquiring spatio-temporal states of an action is the most crucial step for action classification. In this paper, we propose a data level fusion strategy, Motion Fused Frames (MFFs), designed to fuse motion information... 详细信息
来源: 评论
Essentials for Class Incremental Learning
Essentials for Class Incremental Learning
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Mittal, Sudhanshu Galesso, Silvio Brox, Thomas Univ Freiburg Freiburg Germany
Contemporary neural networks are limited in their ability to learn from evolving streams of training data. When trained sequentially on new or evolving tasks, their accuracy drops sharply, making them unsuitable for m... 详细信息
来源: 评论
Alleviating Representational Shift for Continual Fine-tuning
Alleviating Representational Shift for Continual Fine-tuning
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Jie, Shibo Deng, Zhi-Hong Li, Ziheng Peking Univ Sch Artificial Intelligence Beijing Peoples R China
We study a practical setting of continual learning: fine-tuning on a pre-trained model continually. Previous work has found that, when training on new tasks, the features (penultimate layer representations) of previou... 详细信息
来源: 评论
Contrastive Learning for Sports Video: Unsupervised Player Classification
Contrastive Learning for Sports Video: Unsupervised Player C...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Koshkina, Maria Pidaparthy, Hemanth Elder, James H. York Univ Toronto ON Canada
We address the problem of unsupervised classification of players in a team sport according to their team affiliation, when jersey colours and design are not known a priori. We adopt a contrastive learning approach in ... 详细信息
来源: 评论
Scaled 360 layouts: Revisiting non-central panoramas
Scaled 360 layouts: Revisiting non-central panoramas
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Berenguel-Baeta, Bruno Bermudez-Cameo, Jesus Guerrero, Jose J. Univ Zaragoza I3A Zaragoza Spain
From a non-central panorama, 3D lines can be recovered by geometric reasoning. However, their sensitivity to noise and the complex geometric modeling required has led these panoramas being very little investigated. In... 详细信息
来源: 评论
Instagram Filter Removal on Fashionable Images
Instagram Filter Removal on Fashionable Images
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Kinli, Furkan Ozcan, Baris Kirac, Furkan Ozyegin Univ Video Vis & Graph Lab Istanbul Turkey
Social media images are generally transformed by filtering to obtain aesthetically more pleasing appearances. However, CNNs generally fail to interpret both the image and its filtered version as the same in the visual... 详细信息
来源: 评论
Multi-view Multi-label Canonical Correlation Analysis for Cross-modal Matching and Retrieval
Multi-view Multi-label Canonical Correlation Analysis for Cr...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Sanghavi, Rushil Verma, Yashaswi IIT Jodhpur Jodhpur Rajasthan India
In this paper, we address the problem of cross-modal retrieval in presence of multi-view and multi-label data. For this, we present Multi-view Multi-label Canonical Correlation Analysis (or MVMLCCA), which is a genera... 详细信息
来源: 评论