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检索条件"任意字段=IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops"
12859 条 记 录,以下是4771-4780 订阅
排序:
A Dual Iterative Refinement Method for Non-rigid Shape Matching
A Dual Iterative Refinement Method for Non-rigid Shape Match...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Xiang, Rui Lai, Rongjie Zhao, Hongkai UC Dept Math Irvine CA 92697 USA Rensselaer Polytech Inst Dept Math Troy NY 12181 USA Duke Univ Dept Math Durham NC 27706 USA
In this work, a robust and efficient dual iterative refinement (DIR) method is proposed for dense correspondence between two nearly isometric shapes. The key idea is to use dual information, such as spatial and spectr... 详细信息
来源: 评论
Shadow Removal via Global Residual Free Unet and Shadow Generation
Shadow Removal via Global Residual Free Unet and Shadow Gene...
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ieee computer Society conference on computer vision and pattern recognition workshops (CVPRW)
作者: Dong Li Xin Lu Yurui Zhu Xi Wang Jie Xiao Yunpeng Zhang Xueyang Fu Zheng-Jun Zha University of Science and Technology of China
Existing shadow removal methods face challenges when confronted with real-world scenes, particularly when dealing with complex background information and high-resolution images. To address these issues, we present a s... 详细信息
来源: 评论
Photorealistic Arm Robot Simulation for 3D Plant Reconstruction and Automatic Annotation using Unreal Engine 5
Photorealistic Arm Robot Simulation for 3D Plant Reconstruct...
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ieee computer Society conference on computer vision and pattern recognition workshops (CVPRW)
作者: Xingjian Li Jeremy Park Chris Reberg-Horton Steven Mirsky Edgar Lobaton Lirong Xiang Department of Biological and Agricultural Engineering North Carolina State University Department of Electrical and Computer Engineering North Carolina State University Department of Computer Science North Carolina State University Department of Crop and Soil Science North Carolina State University Sustainable Agricultural Systems Laboratory USDA-ARS
Robotics paired with computer vision are widely used in precision agriculture. Simulations are critical for safety and performance estimation by verifying their routine in a virtual world before real-world testing and... 详细信息
来源: 评论
Multiresolution Knowledge Distillation for Anomaly Detection
Multiresolution Knowledge Distillation for Anomaly Detection
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Salehi, Mohammadreza Sadjadi, Niousha Baselizadeh, Soroosh Rohban, Mohammad H. Rabiee, Hamid R. Sharif Univ Technol Dept Comp Engn Tehran Iran
Unsupervised representation learning has proved to be a critical component of anomaly detection/localization in images. The challenges to learn such a representation are two-fold. Firstly, the sample size is not often... 详细信息
来源: 评论
PCLs: Geometry-aware Neural Reconstruction of 3D Pose with Perspective Crop Layers
PCLs: Geometry-aware Neural Reconstruction of 3D Pose with P...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Yu, Frank Salzmann, Mathieu Fua, Pascal Rhodin, Helge Univ British Columbia Vancouver BC Canada Ecole Polytech Fed Lausanne Lausanne Switzerland
Local processing is an essential feature of CNNs and other neural network architectures-it is one of the reasons why they work so well on images where relevant information is, to a large extent, local. However, perspe... 详细信息
来源: 评论
Generalizing to the Open World: Deep Visual Odometry with Online Adaptation
Generalizing to the Open World: Deep Visual Odometry with On...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Li, Shunkai Wu, Xin Cao, Yingdian Zha, Hongbin Peking Univ Sch EECS Key Lab Machine Percept MOE PKU SenseTime Machine Vis Joint Lab Beijing Peoples R China
Despite learning-based visual odometry (VO) has shown impressive results in recent years, the pretrained networks may easily collapse in unseen environments. The large domain gap between training and testing data make... 详细信息
来源: 评论
HistoGAN: Controlling Colors of GAN-Generated and Real Images via Color Histograms
HistoGAN: Controlling Colors of GAN-Generated and Real Image...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Afifi, Mahmoud Brubaker, Marcus A. Brown, Michael S. York Univ N York ON Canada
While generative adversarial networks (GANs) can successfully produce high-quality images, they can be challenging to control. Simplifying GAN-based image generation is critical for their adoption in graphic design an... 详细信息
来源: 评论
Image-to-image Translation via Hierarchical Style Disentanglement
Image-to-image Translation via Hierarchical Style Disentangl...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Li, Xinyang Zhang, Shengchuan Hu, Jie Cao, Liujuan Hong, Xiaopeng Mao, Xudong Huang, Feiyue Wu, Yongjian Ji, Rongrong Xiamen Univ Sch Informat Xiamen Peoples R China Xi An Jiao Tong Univ Xian Peoples R China Peng Cheng Lab Shenzhen Peoples R China Xiamen Univ Tencent Youtu Lab Xiamen Peoples R China Xiamen Univ Inst Artificial Intelligence Xiamen Peoples R China
Recently, image-to-image translation has made significant progress in achieving both multi-label (i.e., translation conditioned on different labels) and multi-style (i.e., generation with diverse styles) tasks. Howeve... 详细信息
来源: 评论
Revisiting Superpixels for Active Learning in Semantic Segmentation with Realistic Annotation Costs
Revisiting Superpixels for Active Learning in Semantic Segme...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Cai, Lile Xu, Xun Liew, Jun Hao Foo, Chuan Sheng Inst Infocomm Res Singapore Singapore Natl Univ Singapore Singapore Singapore
State-of-the-art methods for semantic segmentation are based on deep neural networks that are known to be data-hungry. Region-based active learning has shown to be a promising method for reducing data annotation costs... 详细信息
来源: 评论
Causal Attention for vision-Language Tasks
Causal Attention for Vision-Language Tasks
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Yang, Xu Zhang, Hanwang Qi, Guojun Cai, Jianfei Nanyang Technol Univ Sch Comp Sci & Engn Singapore Singapore Futurewei Technol Santa Clara CA USA Monash Univ Fac Informat Technol Clayton Vic Australia
We present a novel attention mechanism: Causal Attention (CATT), to remove the ever-elusive confounding effect in existing attention-based vision-language models. This effect causes harmful bias that misleads the atte... 详细信息
来源: 评论