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检索条件"任意字段=Conference on Computer Vision and Pattern Recognition"
30988 条 记 录,以下是4731-4740 订阅
排序:
Transferable Semantic Augmentation for Domain Adaptation
Transferable Semantic Augmentation for Domain Adaptation
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Li, Shuang Xie, Mixue Gong, Kaixiong Liu, Chi Harold Wang, Yulin Li, Wei Beijing Inst Technol Beijing Peoples R China Tsinghua Univ Beijing Peoples R China Inceptio Tech Fremont CA USA
Domain adaptation has been widely explored by transferring the knowledge from a label-rich source domain to a related but unlabeled target domain. Most existing domain adaptation algorithms attend to adapting feature ... 详细信息
来源: 评论
Graph-based High-Order Relation Discovery for Fine-grained recognition
Graph-based High-Order Relation Discovery for Fine-grained R...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Zhao, Yifan Yan, Ke Huang, Feiyue Li, Jia Beihang Univ State Key Lab Virtual Real Technol & Syst SCSE Beijing Peoples R China Tencent Youtu Lab Shanghai Peoples R China Peng Cheng Lab Shenzhen Peoples R China
Fine-grained object recognition aims to learn effective features that can identify the subtle differences between visually similar objects. Most of the existing works tend to amplify discriminative part regions with a... 详细信息
来源: 评论
NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections
NeRF in the Wild: Neural Radiance Fields for Unconstrained P...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Martin-Brualla, Ricardo Radwan, Noha Sajjadi, Mehdi S. M. Barron, Jonathan T. Dosovitskiy, Alexey Duckworth, Daniel Google Res Mountain View CA 94043 USA
We present a learning-based method for synthesizing novel views of complex scenes using only unstructured collections of in-the-wild photographs. We build on Neural Radiance Fields (NeRF), which uses the weights of a ... 详细信息
来源: 评论
Progressive Semantic Segmentation
Progressive Semantic Segmentation
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Chuong Huynh Anh Tuan Tran Khoa Luu Minh Hoai VinAI Res Hanoi Vietnam VinUniversity Hanoi Vietnam Univ Arkansas Fayetteville AR 72701 USA SUNY Stony Brook Stony Brook NY 11790 USA
The objective of this work is to segment high-resolution images without overloading GPU memory usage or losing the fine details in the output segmentation map. The memory constraint means that we must either downsampl... 详细信息
来源: 评论
AdvSim: Generating Safety-Critical Scenarios for Self-Driving Vehicles
AdvSim: Generating Safety-Critical Scenarios for Self-Drivin...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Wang, Jingkang Pun, Ava Tu, James Manivasagam, Sivabalan Sadat, Abbas Casas, Sergio Ren, Mengye Urtasun, Raquel Univ Toronto Toronto ON Canada Uber ATG Pittsburgh PA 15201 USA Univ Waterloo Waterloo ON Canada
As self-driving systems become better, simulating scenarios where the autonomy stack may fail becomes more important. Traditionally, those scenarios are generated for a few scenes with respect to the planning module t... 详细信息
来源: 评论
Gender Detection Using Machine Learning  15th
Gender Detection Using Machine Learning
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15th International conference on Soft Computing and pattern recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2023
作者: Anwesh, Ramineni Uday, Ch Ravinder, Nellutla Morla, Ramya Vignesh, Karanam Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Green Fields Guntur District Andhra Pradesh Vaddeswaram India
One of the most important aspects of computer vision and machine learning nowadays is gender detection through picture recognition, which has profound consequences for practical applications. This study uses the power... 详细信息
来源: 评论
Yoga Posture Prediction Using Invariant Moments and Machine Learning Techniques  15th
Yoga Posture Prediction Using Invariant Moments and Machine...
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15th International conference on Soft Computing and pattern recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2023
作者: Thushara, L. Abdul Jabbar, P. School of Computer Sciences Mahatma Gandhi University Kerala India
In recent years, the intersection of computer vision and yoga practice has emerged as a promising area of research, focusing on developing automated systems for accurate recognition and analysis of yoga postures. Acti... 详细信息
来源: 评论
Towards Fair Federated Learning with Zero-Shot Data Augmentation
Towards Fair Federated Learning with Zero-Shot Data Augmenta...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Hao, Weituo El-Khamy, Mostafa Lee, Jungwon Zhang, Jianyi Liang, Kevin J. Chen, Changyou Carin, Lawrence Duke Univ Durham NC 27706 USA Samsung Suwon South Korea SUNY Buffalo Buffalo NY USA
Federated learning has emerged as an important distributed learning paradigm, where a server aggregates a global model from many client-trained models, while having no access to the client data. Although it is recogni... 详细信息
来源: 评论
Discovering Multi-Hardware Mobile Models via Architecture Search
Discovering Multi-Hardware Mobile Models via Architecture Se...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Chu, Grace Arikan, Okan Bender, Gabriel Wang, Weijun Brighton, Achille Kindermans, Pieter-Jan Liu, Hanxiao Akin, Berkin Gupta, Suyog Howard, Andrew Google LLC Mountain View CA 94043 USA
Hardware-aware neural architecture designs have been predominantly focusing on optimizing model performance on single hardware and model development complexity, where another important factor, model deployment complex... 详细信息
来源: 评论
BasisNet: Two-stage Model Synthesis for Efficient Inference
BasisNet: Two-stage Model Synthesis for Efficient Inference
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Zhang, Mingda Chu, Chun-Te Zhmoginov, Andrey Howard, Andrew Jou, Brendan Zhu, Yukun Zhang, Li Hwa, Rebecca Kovashka, Adriana Univ Pittsburgh Dept Comp Sci Pittsburgh PA 15260 USA Google Res Mountain View CA 94043 USA
In this work, we present BasisNet which combines recent advancements in efficient neural network architectures, conditional computation, and early termination in a simple new form. Our approach incorporates a lightwei... 详细信息
来源: 评论