咨询与建议

限定检索结果

文献类型

  • 22,998 篇 会议
  • 93 篇 期刊文献
  • 4 册 图书

馆藏范围

  • 23,094 篇 电子文献
  • 1 种 纸本馆藏

日期分布

学科分类号

  • 13,621 篇 工学
    • 11,107 篇 计算机科学与技术...
    • 3,478 篇 软件工程
    • 2,445 篇 机械工程
    • 1,715 篇 光学工程
    • 1,076 篇 电气工程
    • 1,013 篇 控制科学与工程
    • 784 篇 信息与通信工程
    • 411 篇 仪器科学与技术
    • 352 篇 生物工程
    • 251 篇 生物医学工程(可授...
    • 196 篇 电子科学与技术(可...
    • 114 篇 化学工程与技术
    • 107 篇 安全科学与工程
    • 100 篇 测绘科学与技术
    • 88 篇 建筑学
    • 85 篇 交通运输工程
    • 84 篇 土木工程
  • 3,494 篇 医学
    • 3,481 篇 临床医学
    • 81 篇 基础医学(可授医学...
  • 3,240 篇 理学
    • 1,939 篇 物理学
    • 1,639 篇 数学
    • 563 篇 统计学(可授理学、...
    • 500 篇 生物学
    • 249 篇 系统科学
    • 106 篇 化学
  • 521 篇 管理学
    • 311 篇 图书情报与档案管...
    • 223 篇 管理科学与工程(可...
    • 76 篇 工商管理
  • 276 篇 艺术学
    • 276 篇 设计学(可授艺术学...
  • 66 篇 法学
    • 63 篇 社会学
  • 38 篇 农学
  • 28 篇 教育学
  • 22 篇 经济学
  • 10 篇 军事学
  • 3 篇 文学

主题

  • 10,186 篇 computer vision
  • 3,919 篇 pattern recognit...
  • 3,005 篇 training
  • 2,007 篇 computational mo...
  • 1,817 篇 visualization
  • 1,815 篇 cameras
  • 1,515 篇 feature extracti...
  • 1,481 篇 shape
  • 1,455 篇 three-dimensiona...
  • 1,438 篇 image segmentati...
  • 1,287 篇 robustness
  • 1,205 篇 computer archite...
  • 1,155 篇 semantics
  • 1,147 篇 conferences
  • 1,107 篇 layout
  • 1,093 篇 computer science
  • 1,088 篇 object detection
  • 1,025 篇 benchmark testin...
  • 970 篇 codes
  • 923 篇 face recognition

机构

  • 136 篇 univ sci & techn...
  • 121 篇 univ chinese aca...
  • 118 篇 chinese univ hon...
  • 109 篇 carnegie mellon ...
  • 101 篇 tsinghua univers...
  • 100 篇 microsoft resear...
  • 95 篇 swiss fed inst t...
  • 93 篇 zhejiang univ pe...
  • 82 篇 university of sc...
  • 81 篇 zhejiang univers...
  • 81 篇 university of ch...
  • 77 篇 shanghai ai lab ...
  • 72 篇 shanghai jiao to...
  • 69 篇 national laborat...
  • 68 篇 microsoft res as...
  • 67 篇 alibaba grp peop...
  • 64 篇 adobe research
  • 64 篇 tsinghua univ pe...
  • 60 篇 peking univ peop...
  • 59 篇 univ oxford oxfo...

作者

  • 81 篇 van gool luc
  • 72 篇 timofte radu
  • 64 篇 zhang lei
  • 47 篇 luc van gool
  • 40 篇 yang yi
  • 40 篇 li stan z.
  • 37 篇 loy chen change
  • 34 篇 chen chen
  • 33 篇 qi tian
  • 32 篇 liu yang
  • 32 篇 xiaoou tang
  • 32 篇 sun jian
  • 31 篇 tian qi
  • 30 篇 murino vittorio
  • 30 篇 pascal fua
  • 29 篇 darrell trevor
  • 29 篇 li fei-fei
  • 28 篇 li xin
  • 28 篇 ying shan
  • 27 篇 vasconcelos nuno

语言

  • 23,028 篇 英文
  • 38 篇 其他
  • 22 篇 中文
  • 5 篇 土耳其文
  • 2 篇 日文
检索条件"任意字段=IEEE Conference on Computer Vision and Pattern Recognition Workshops"
23095 条 记 录,以下是4861-4870 订阅
排序:
Fast and Accurate Model Scaling
Fast and Accurate Model Scaling
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Dollar, Piotr Singh, Mannat Girshick, Ross Facebook AI Res FAIR Menlo Pk CA 94025 USA
In this work we analyze strategies for convolutional neural network scaling;that is, the process of scaling a base convolutional network to endow it with greater computational complexity and consequently representatio... 详细信息
来源: 评论
Temporally-Weighted Hierarchical Clustering for Unsupervised Action Segmentation
Temporally-Weighted Hierarchical Clustering for Unsupervised...
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Sarfraz, M. Saquib Murray, Naila Sharma, Vivek Diba, Ali van Gool, Luc Stiefelhagen, Rainer Karlsruhe Inst Technol Karlsruhe Germany Facebook AI Res Menlo Pk CA USA MIT Cambridge MA 02139 USA Harvard Med Sch Boston MA 02115 USA Katholieke Univ Leuven Leuven Belgium Swiss Fed Inst Technol Zurich Switzerland Daimler TSS Ulm Germany
Action segmentation refers to inferring boundaries of semantically consistent visual concepts in videos and is an important requirement for many video understanding tasks. For this and other video understanding tasks,... 详细信息
来源: 评论
NBNet: Noise Basis Learning for Image Denoising with Subspace Projection
NBNet: Noise Basis Learning for Image Denoising with Subspac...
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Cheng, Shen Wang, Yuzhi Huang, Haibin Liu, Donghao Fan, Haoqiang Liu, Shuaicheng Megvii Technol Beijing Peoples R China Kuaishou Technol Beijing Peoples R China Univ Elect Sci & Technol China Chengdu Peoples R China
In this paper, we introduce NBNet, a novel framework for image denoising. Unlike previous works, we propose to tackle this challenging problem from a new perspective: noise reduction by image-adaptive projection. Spec... 详细信息
来源: 评论
Learning To Count Everything
Learning To Count Everything
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Ranjan, Viresh Sharma, Udbhav Thu Nguyen Hoai, Minh SUNY Stony Brook Stony Brook NY 11794 USA VinAI Res Hanoi Vietnam
Existing works on visual counting primarily focus on one specific category at a time, such as people, animals, and cells. In this paper, we are interested in counting everything, that is to count objects from any cate... 详细信息
来源: 评论
Learning Progressive Point Embeddings for 3D Point Cloud Generation
Learning Progressive Point Embeddings for 3D Point Cloud Gen...
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Wen, Cheng Yu, Baosheng Tao, Dacheng Univ Sydney Fac Engn Sch Comp Sci 6 Cleveland St Darlington NSW 2008 Australia
Generative models for 3D point clouds are extremely important for scene/object reconstruction applications in autonomous driving and robotics. Despite recent success of deep learning-based representation learning, it ... 详细信息
来源: 评论
Sparse Multi-Path Corrections in Fringe Projection Profilometry
Sparse Multi-Path Corrections in Fringe Projection Profilome...
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Zhang, Yu Lau, Daniel Wipf, David Nanjing Univ Nanjing Peoples R China Univ Kentucky Lexington KY 40506 USA Amazon Seattle WA USA
Three-dimensional scanning by means of structured light illumination is an active imaging technique involving projecting and capturing a series of striped patterns and then using the observed warping of stripes to rec... 详细信息
来源: 评论
Double low-rank representation with projection distance penalty for clustering
Double low-rank representation with projection distance pena...
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Fu, Zhiqiang Zhao, Yao Chang, Dongxia Zhang, Xingxing Wang, Yiming Beijing Jiaotong Univ Inst Informat Sci Beijing Peoples R China Beijing Key Lab Adv Informat Sci & Network Techno Beijing Peoples R China Tsinghua Univ Dept Comp Sci & Technol Beijing Peoples R China
This paper presents a novel, simple yet robust self-representation method, i.e., Double Low-Rank Representation with Projection Distance penalty (DLRRPD) for clustering. With the learned optimal projected representati... 详细信息
来源: 评论
Enhance Curvature Information by Structured Stochastic Quasi-Newton Methods
Enhance Curvature Information by Structured Stochastic Quasi...
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Yang, Minghan Xu, Dong Chen, Hongyu Wen, Zaiwen Chen, Mengyun Peking Univ Sch Math Sci Beijing Peoples R China Peking Univ Beijing Int Ctr Math Res Beijing Peoples R China Peking Univ Ctr Data Sci Beijing Peoples R China Peking Univ Natl Engn Lab Big Data Anal & Applicat Beijing Peoples R China Huawei Technol Co Ltd Shenzhen Peoples R China
In this paper, we consider stochastic second-order methods for minimizing a finite summation of nonconvex functions. One important key is to find an ingenious but cheap scheme to incorporate local curvature informatio... 详细信息
来源: 评论
StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation
StyleSpace Analysis: Disentangled Controls for StyleGAN Imag...
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Wu, Zongze Lischinski, Dani Shechtman, Eli Hebrew Univ Jerusalem Jerusalem Israel Adobe Res San Jose CA USA
We explore and analyze the latent style space of StyleGAN2, a state-of-the-art architecture for image generation, using models pretrained on several different datasets. We first show that StyleSpace, the space of chan... 详细信息
来源: 评论
Stochastic Whitening Batch Normalization
Stochastic Whitening Batch Normalization
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Zhang, Shengdong Nezhadarya, Ehsan Fashandi, Homa Liu, Jiayi Graham, Darin Shah, Mohak LG Elect Canada Toronto AI Lab Toronto ON Canada LG Elect USA Amer R&D Lab Santa Clara CA USA
Batch Normalization (BN) is a popular technique for training Deep Neural Networks (DNNs). BN uses scaling and shifting to normalize activations of mini-batches to accelerate convergence and improve generalization. The... 详细信息
来源: 评论