咨询与建议

限定检索结果

文献类型

  • 11,745 篇 会议
  • 8 篇 期刊文献

馆藏范围

  • 11,753 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 8,139 篇 工学
    • 7,674 篇 计算机科学与技术...
    • 804 篇 机械工程
    • 580 篇 软件工程
    • 376 篇 电气工程
    • 252 篇 控制科学与工程
    • 208 篇 光学工程
    • 85 篇 生物工程
    • 83 篇 信息与通信工程
    • 29 篇 生物医学工程(可授...
    • 23 篇 电子科学与技术(可...
    • 21 篇 化学工程与技术
    • 15 篇 交通运输工程
    • 14 篇 安全科学与工程
    • 10 篇 网络空间安全
    • 8 篇 仪器科学与技术
    • 6 篇 材料科学与工程(可...
    • 6 篇 动力工程及工程热...
  • 3,194 篇 医学
    • 3,190 篇 临床医学
    • 11 篇 基础医学(可授医学...
    • 7 篇 公共卫生与预防医...
  • 481 篇 理学
    • 216 篇 物理学
    • 203 篇 系统科学
    • 88 篇 生物学
    • 55 篇 数学
    • 29 篇 统计学(可授理学、...
    • 24 篇 化学
  • 55 篇 管理学
    • 29 篇 图书情报与档案管...
    • 28 篇 管理科学与工程(可...
    • 12 篇 工商管理
  • 17 篇 法学
    • 15 篇 社会学
  • 6 篇 农学
  • 4 篇 教育学
  • 2 篇 经济学
  • 1 篇 军事学
  • 1 篇 艺术学

主题

  • 5,434 篇 computer vision
  • 2,516 篇 training
  • 2,087 篇 pattern recognit...
  • 1,621 篇 computational mo...
  • 1,435 篇 visualization
  • 1,306 篇 three-dimensiona...
  • 1,060 篇 semantics
  • 981 篇 codes
  • 968 篇 benchmark testin...
  • 898 篇 computer archite...
  • 884 篇 deep learning
  • 762 篇 task analysis
  • 681 篇 feature extracti...
  • 536 篇 face recognition
  • 527 篇 conferences
  • 515 篇 transformers
  • 515 篇 neural networks
  • 479 篇 object detection
  • 466 篇 image segmentati...
  • 454 篇 cameras

机构

  • 168 篇 univ sci & techn...
  • 144 篇 univ chinese aca...
  • 144 篇 tsinghua univ pe...
  • 143 篇 carnegie mellon ...
  • 135 篇 chinese univ hon...
  • 112 篇 peng cheng lab p...
  • 108 篇 zhejiang univ pe...
  • 97 篇 swiss fed inst t...
  • 92 篇 tsinghua univers...
  • 92 篇 sensetime res pe...
  • 88 篇 shanghai ai lab ...
  • 85 篇 zhejiang univers...
  • 84 篇 shanghai jiao to...
  • 78 篇 peng cheng labor...
  • 77 篇 university of sc...
  • 77 篇 alibaba grp peop...
  • 76 篇 univ hong kong p...
  • 76 篇 tech univ munich...
  • 76 篇 stanford univ st...
  • 73 篇 university of ch...

作者

  • 76 篇 timofte radu
  • 64 篇 van gool luc
  • 50 篇 zhang lei
  • 44 篇 yang yi
  • 40 篇 loy chen change
  • 34 篇 tao dacheng
  • 32 篇 liu yang
  • 32 篇 chen chen
  • 30 篇 zhou jie
  • 30 篇 tian qi
  • 30 篇 sun jian
  • 28 篇 zha zheng-jun
  • 27 篇 qi tian
  • 26 篇 li xin
  • 26 篇 vasconcelos nuno
  • 26 篇 ying shan
  • 25 篇 liu xiaoming
  • 25 篇 luc van gool
  • 25 篇 boxin shi
  • 24 篇 zheng wei-shi

语言

  • 11,746 篇 英文
  • 7 篇 其他
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
排序:
Guided Integrated Gradients: an Adaptive Path Method for Removing Noise
Guided Integrated Gradients: an Adaptive Path Method for Rem...
收藏 引用
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
Learning Imbalanced Data with vision Transformers
Learning Imbalanced Data with Vision Transformers
收藏 引用
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
clDice - a Novel Topology-Preserving Loss Function for Tubular Structure Segmentation
clDice - a Novel Topology-Preserving Loss Function for Tubul...
收藏 引用
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
来源: 评论
Research on Identifying Differential Behavior in Complex Scenarios  39
Research on Identifying Differential Behavior in Complex Sce...
收藏 引用
39th Youth Academic Annual conference of Chinese-Association-of-Automation (YAC)
作者: Zhao, Shitao Fang, Kai Feng, Zihao China Acad Railway Sci Inst Comp Technol Beijing Peoples R China
Group behavior recognition is a significant research area in computer vision and pattern recognition. However, recognizing an individual who behaves differently from the majority in complex scenes, such as malls and t... 详细信息
来源: 评论
Stay Positive: Non-Negative Image Synthesis for Augmented Reality
Stay Positive: Non-Negative Image Synthesis for Augmented Re...
收藏 引用
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
来源: 评论
PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds
PAConv: Position Adaptive Convolution with Dynamic Kernel As...
收藏 引用
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
来源: 评论
TrafficSim: Learning to Simulate Realistic Multi-Agent Behaviors
TrafficSim: Learning to Simulate Realistic Multi-Agent Behav...
收藏 引用
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
Intelligent Carpet: Inferring 3D Human Pose from Tactile Signals
Intelligent Carpet: Inferring 3D Human Pose from Tactile Sig...
收藏 引用
ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Luo, Yiyue Li, Yunzhu Foshey, Michael Shou, Wan Sharma, Pratyusha Palacios, Tomas Torralba, Antonio Matusik, Wojciech MIT Cambridge MA 02139 USA
Daily human activities, e.g., locomotion, exercises, and resting, are heavily guided by the tactile interactions between the human and the ground. In this work, leveraging such tactile interactions, we propose a 3D hu... 详细信息
来源: 评论
Action Shuffle Alternating Learning for Unsupervised Action Segmentation
Action Shuffle Alternating Learning for Unsupervised Action ...
收藏 引用
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
Learning Continuous Image Representation with Local Implicit Image Function
Learning Continuous Image Representation with Local Implicit...
收藏 引用
ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Chen, Yinbo Liu, Sifei Wang, Xiaolong Univ Calif San Diego La Jolla CA 92093 USA NVIDIA Santa Clara CA USA
How to represent an image? While the visual world is presented in a continuous manner, machines store and see the images in a discrete way with 2D arrays of pixels. In this paper, we seek to learn a continuous represe... 详细信息
来源: 评论