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检索条件"任意字段=Conference on Computer Vision and Pattern Recognition"
29687 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
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
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
Research on photovoltaic power generation project progress drone identification system based on computer convolutional neural network  2
Research on photovoltaic power generation project progress d...
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2nd International conference on Mechatronics, IoT and Industrial Informatics, ICMIII 2024
作者: Wang, Yong Min, Xiangli Chen, Guang Fu, Wenjie Fu, Jiangque Yi, Le'an Jiang, Qiao Li, Hongming China Energy Jiangxi New Energy Industry Co. Ltd Nanchang China China Energy Investment Group Jiangxi Power Co. Ltd Nanchang China Ctrl. S. China Electric Power Design Institute Co. Ltd. of China Power Engineering Consulting Group Wuhan China
This study aims to develop an innovative computer convolutional neural network (CNN) UAV recognition system for the progress of photovoltaic power generation projects. Its core goal is to use the rich visual data coll... 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
Smoothing the Disentangled Latent Style Space for Unsupervised Image-to-Image Translation
Smoothing the Disentangled Latent Style Space for Unsupervis...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Liu, Yahui Sangineto, Enver Chen, Yajing Bao, Linchao Zhang, Haoxian Sebe, Nicu Lepri, Bruno Wang, Wei De Nadai, Marco Univ Trento Trento Italy Tencent AI Lab Shenzhen Peoples R China Fdn Bruno Kessler Povo Italy
Image-to-Image (I2I) multi-domain translation models are usually evaluated also using the quality of their semantic interpolation results. However, state-of-the-art models frequently show abrupt changes in the image a... 详细信息
来源: 评论
Depth Completion with Twin Surface Extrapolation at Occlusion Boundaries
Depth Completion with Twin Surface Extrapolation at Occlusio...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Imran, Saif Liu, Xiaoming Morris, Daniel Michigan State Univ E Lansing MI 48824 USA
Depth completion starts from a sparse set of known depth values and estimates the unknown depths for the remaining image pixels. Most methods model this as depth interpolation and erroneously interpolate depth pixels ... 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
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