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检索条件"任意字段=IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops"
12857 条 记 录,以下是4791-4800 订阅
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Unsupervised Degradation Representation Learning for Blind Super-Resolution
Unsupervised Degradation Representation Learning for Blind S...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Wang, Longguang Wang, Yingqian Dong, Xiaoyu Xu, Qingyu Yang, Jungang An, Wei Guo, Yulan Natl Univ Def Technol Changsha Peoples R China Univ Tokyo Tokyo Japan RIKEN AIP Tokyo Japan
Most existing CNN-based super-resolution (SR) methods are developed based on an assumption that the degradation is fixed and known (e.g., bicubic downsampling). However, these methods suffer a severe performance drop ... 详细信息
来源: 评论
Equalization Loss v2: A New Gradient Balance Approach for Long-tailed Object Detection
Equalization Loss v2: A New Gradient Balance Approach for Lo...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Tan, Jingru Lu, Xin Zhang, Gang Yin, Changqing Li, Quanquan Tongji Univ Shanghai Peoples R China SenseTime Res Hong Kong Peoples R China Tsinghua Univ Beijing Peoples R China
Recently proposed decoupled training methods emerge as a dominant paradigm for long-tailed object detection. But they require an extra fine-tuning stage, and the disjointed optimization of representation and classifie... 详细信息
来源: 评论
Scene-aware Generative Network for Human Motion Synthesis
Scene-aware Generative Network for Human Motion Synthesis
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Wang, Jingbo Yan, Sijie Dai, Bo Lin, Dahua Chinese Univ Hong Kong CUHK SenseTime Joint Lab Hong Kong Peoples R China Nanyang Technol Univ S Lab Singapore Singapore Ctr Perceptual & Interact Intelligence Hong Kong Peoples R China Chinese Univ Hong Kong Hong Kong Peoples R China
We revisit human motion synthesis, a task useful in various real-world applications, in this paper. Whereas a number of methods have been developed previously for this task, they are often limited in two aspects: 1) f... 详细信息
来源: 评论
Open-Vocabulary Object Detection Using Captions
Open-Vocabulary Object Detection Using Captions
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Zareian, Alireza Dela Rosa, Kevin Hu, Derek Hao Chang, Shih-Fu Snap Inc Seattle WA 98121 USA Columbia Univ New York NY 10027 USA
Despite the remarkable accuracy of deep neural networks in object detection, they are costly to train and scale due to supervision requirements. Particularly, learning more object categories typically requires proport... 详细信息
来源: 评论
The New Agronomists: Language Models are Experts in Crop Management
The New Agronomists: Language Models are Experts in Crop Man...
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ieee computer Society conference on computer vision and pattern recognition workshops (CVPRW)
作者: Jing Wu Zhixin Lai Suiyao Chen Ran Tao Pan Zhao Naira Hovakimyan University of Illinois at Urbana-Champaign Cornell University University of South Florida University of Alabama
Crop management plays a crucial role in determining crop yield, economic profitability, and environmental sustainability. Despite the availability of management guidelines, optimizing these practices remains a complex... 详细信息
来源: 评论
Greedy Hierarchical Variational Autoencoders for Large-Scale Video Prediction
Greedy Hierarchical Variational Autoencoders for Large-Scale...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Wu, Bohan Nair, Suraj Martin-Martin, Roberto Li Fei-Fei Finn, Chelsea Stanford Univ Stanford CA 94305 USA
A video prediction model that generalizes to diverse scenes would enable intelligent agents such as robots to perform a variety of tasks via planning with the model. However, while existing video prediction models hav... 详细信息
来源: 评论
Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place recognition
Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descript...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Hausler, Stephen Garg, Sourav Xu, Ming Milford, Michael Fischer, Tobias Queensland Univ Technol QUT Ctr Robot Brisbane Qld Australia
Visual Place recognition is a challenging task for robotics and autonomous systems, which must deal with the twin problems of appearance and viewpoint change in an always changing world. This paper introduces Patch-Ne... 详细信息
来源: 评论
Synthesizing Long-Term 3D Human Motion and Interaction in 3D Scenes
Synthesizing Long-Term 3D Human Motion and Interaction in 3D...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Wang, Jiashun Xu, Huazhe Xu, Jingwei Liu, Sifei Wang, Xiaolong Univ Calif San Diego San Diego CA 92093 USA Univ Calif Berkeley Berkeley CA USA Shanghai Jiao Tong Univ Shanghai Peoples R China NVIDIA Santa Clara CA USA
Synthesizing 3D human motion plays an important role in many graphics applications as well as understanding human activity. While many efforts have been made on generating realistic and natural human motion, most appr... 详细信息
来源: 评论
Orthogonal Over-Parameterized Training
Orthogonal Over-Parameterized Training
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Liu, Weiyang Lin, Rongmei Liu, Zhen Rehg, James M. Paull, Liam Xiong, Li Song, Le Weller, Adrian Univ Cambridge Cambridge England Max Planck Inst Intelligent Syst Stuttgart Germany Emory Univ Atlanta GA 30322 USA Univ Montreal Mila Montreal PQ Canada Georgia Inst Technol Atlanta GA 30332 USA Alan Turing Inst London England
The inductive bias of a neural network is largely determined by the architecture and the training algorithm. To achieve good generalization, how to effectively train a neural network is of great importance. We propose... 详细信息
来源: 评论
Learnable Motion Coherence for Correspondence Pruning
Learnable Motion Coherence for Correspondence Pruning
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Liu, Yuan Liu, Lingjie Lin, Cheng Dong, Zhen Wang, Wenping Univ Hong Kong Hong Kong Peoples R China Saarland Informat Campus MPI Informat Saarbrucken Germany Wuhan Univ Wuhan Peoples R China Texas A&M Univ College Stn TX 77843 USA
Motion coherence is an important clue for distinguishing true correspondences from false ones. Modeling motion coherence on sparse putative correspondences is challenging due to their sparsity and uneven distributions... 详细信息
来源: 评论