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检索条件"任意字段=2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023"
11753 条 记 录,以下是4671-4680 订阅
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On the Importance of Accurate Geometry Data for Dense 3D vision Tasks
On the Importance of Accurate Geometry Data for Dense 3D Vis...
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conference on computer vision and pattern recognition (cvpr)
作者: HyunJun Jung Patrick Ruhkamp Guangyao Zhai Nikolas Brasch Yitong Li Yannick Verdie Jifei Song Yiren Zhou Anil Armagan Slobodan Ilic Ales Leonardis Nassir Navab Benjamin Busam Technical University of Munich 3Dwe.ai Huawei Noah's Ark Lab Siemens AG
Learning-based methods to solve dense 3D vision problems typically train on 3D sensor data. The respectively used principle of measuring distances provides advantages and drawbacks. These are typically not compared no...
来源: 评论
Action Shuffle Alternating Learning for Unsupervised Action Segmentation
Action Shuffle Alternating Learning for Unsupervised Action ...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Li, Jun Todorovic, Sinisa Oregon State Univ Corvallis OR 97331 USA
This paper addresses unsupervised action segmentation. Prior work captures the frame-level temporal structure of videos by a feature embedding that encodes time locations of frames in the video. We advance prior work ... 详细信息
来源: 评论
Point Cloud Upsampling via Disentangled Refinement
Point Cloud Upsampling via Disentangled Refinement
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Li, Ruihui Li, Xianzhi Heng, Pheng-Ann Fu, Chi-Wing Chinese Univ Hong Kong Hong Kong Peoples R China
Point clouds produced by 3D scanning are often sparse, non-uniform, and noisy. Recent upsampling approaches aim to generate a dense point set, while achieving both distribution uniformity and proximity-to-surface, and... 详细信息
来源: 评论
Space-time Neural Irradiance Fields for Free-Viewpoint Video
Space-time Neural Irradiance Fields for Free-Viewpoint Video
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Xian, Wenqi Huang, Jia-Bin Kopf, Johannes Kim, Changil Cornell Tech New York NY 10044 USA Virginia Tech Blacksburg VA USA Facebook Menlo Pk CA USA
We present a method that learns a spatiotemporal neural irradiance field for dynamic scenes from a single video. Our learned representation enables free-viewpoint rendering of the input video. Our method builds upon r... 详细信息
来源: 评论
Learning Imbalanced Data with vision Transformers
Learning Imbalanced Data with Vision Transformers
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conference on computer vision and pattern recognition (cvpr)
作者: Zhengzhuo Xu Ruikang Liu Shuo Yang Zenghao Chai Chun Yuan Shenzhen International Graduate School Tsinghua University China
The real-world data tends to be heavily imbalanced and severely skew the data-driven deep neural networks, which makes Long-Tailed recognition (LTR) a massive challenging task. Existing LTR methods seldom train vision...
来源: 评论
Guided Integrated Gradients: an Adaptive Path Method for Removing Noise
Guided Integrated Gradients: an Adaptive Path Method for Rem...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Kapishnikov, Andrei Venugopalan, Subhashini Avci, Besim Wedin, Ben Terry, Michael Bolukbasi, Tolga Google Res Mountain View CA 94043 USA
Integrated Gradients (IG) [29] is a commonly used feature attribution method for deep neural networks. While IG has many desirable properties, the method often produces spurious/noisy pixel attributions in regions tha... 详细信息
来源: 评论
clDice - a Novel Topology-Preserving Loss Function for Tubular Structure Segmentation
clDice - a Novel Topology-Preserving Loss Function for Tubul...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Shit, Suprosanna Paetzold, Johannes C. Sekuboyina, Anjany Ezhov, Ivan Unger, Alexander Zhylka, Andrey Pluim, Josien P. W. Bauer, Ulrich Menze, Bjoern H. Tech Univ Munich Munich Germany Eindhoven Univ Technol Eindhoven Netherlands
Accurate segmentation of tubular, network-like structures, such as vessels, neurons, or roads, is relevant to many fields of research. For such structures, the topology is their most important characteristic;particula... 详细信息
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Stay Positive: Non-Negative Image Synthesis for Augmented Reality
Stay Positive: Non-Negative Image Synthesis for Augmented Re...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Luo, Katie Yang, Guandao Xian, Wenqi Haraldsson, Harald Hariharan, Bharath Belongie, Serge Cornell Univ Ithaca NY 14853 USA
In applications such as optical see-through and projector augmented reality, producing images amounts to solving non-negative image generation, where one can only add light to an existing image. Most image generation ... 详细信息
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PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds
PAConv: Position Adaptive Convolution with Dynamic Kernel As...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Xu, Mutian Ding, Runyu Zhao, Hengshuang Qi, Xiaojuan Univ Hong Kong Hong Kong Peoples R China Univ Oxford Oxford England
We introduce Position Adaptive Convolution (PAConv), a generic convolution operation for 3D point cloud processing. The key of PAConv is to construct the convolution kernel by dynamically assembling basic weight matri... 详细信息
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TrafficSim: Learning to Simulate Realistic Multi-Agent Behaviors
TrafficSim: Learning to Simulate Realistic Multi-Agent Behav...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Suo, Simon Regalado, Sebastian Casas, Sergio Urtasun, Raquel Uber ATG Pittsburgh PA 15201 USA Univ Toronto Toronto ON Canada Univ Waterloo Waterloo ON Canada
Simulation has the potential to massively scale evaluation of self-driving systems, enabling rapid development as well as safe deployment. Bridging the gap between simulation and the real world requires realistic mult... 详细信息
来源: 评论