咨询与建议

限定检索结果

文献类型

  • 23,136 篇 会议
  • 90 篇 期刊文献
  • 15 册 图书

馆藏范围

  • 23,240 篇 电子文献
  • 1 种 纸本馆藏

日期分布

学科分类号

  • 13,632 篇 工学
    • 11,162 篇 计算机科学与技术...
    • 3,338 篇 软件工程
    • 2,413 篇 机械工程
    • 1,664 篇 光学工程
    • 1,204 篇 电气工程
    • 973 篇 控制科学与工程
    • 738 篇 信息与通信工程
    • 381 篇 仪器科学与技术
    • 322 篇 生物工程
    • 239 篇 生物医学工程(可授...
    • 188 篇 电子科学与技术(可...
    • 109 篇 化学工程与技术
    • 104 篇 安全科学与工程
    • 99 篇 测绘科学与技术
    • 85 篇 建筑学
    • 83 篇 交通运输工程
    • 82 篇 土木工程
    • 56 篇 力学(可授工学、理...
  • 3,695 篇 医学
    • 3,683 篇 临床医学
    • 76 篇 基础医学(可授医学...
  • 3,138 篇 理学
    • 1,880 篇 物理学
    • 1,605 篇 数学
    • 547 篇 统计学(可授理学、...
    • 466 篇 生物学
    • 243 篇 系统科学
    • 107 篇 化学
  • 491 篇 管理学
    • 290 篇 图书情报与档案管...
    • 212 篇 管理科学与工程(可...
    • 74 篇 工商管理
  • 252 篇 艺术学
    • 251 篇 设计学(可授艺术学...
  • 58 篇 法学
  • 38 篇 农学
  • 25 篇 教育学
  • 19 篇 经济学
  • 10 篇 军事学
  • 3 篇 文学

主题

  • 10,396 篇 computer vision
  • 3,893 篇 pattern recognit...
  • 3,101 篇 training
  • 2,104 篇 computational mo...
  • 1,898 篇 visualization
  • 1,800 篇 cameras
  • 1,487 篇 feature extracti...
  • 1,475 篇 three-dimensiona...
  • 1,464 篇 shape
  • 1,447 篇 image segmentati...
  • 1,287 篇 robustness
  • 1,234 篇 computer archite...
  • 1,213 篇 semantics
  • 1,112 篇 benchmark testin...
  • 1,111 篇 conferences
  • 1,104 篇 layout
  • 1,093 篇 object detection
  • 1,085 篇 computer science
  • 1,026 篇 codes
  • 907 篇 face recognition

机构

  • 137 篇 univ sci & techn...
  • 124 篇 univ chinese aca...
  • 121 篇 chinese univ hon...
  • 108 篇 tsinghua univers...
  • 108 篇 carnegie mellon ...
  • 105 篇 microsoft resear...
  • 97 篇 zhejiang univ pe...
  • 91 篇 swiss fed inst t...
  • 85 篇 university of sc...
  • 84 篇 zhejiang univers...
  • 81 篇 shanghai ai lab ...
  • 79 篇 university of ch...
  • 75 篇 shanghai jiao to...
  • 69 篇 microsoft res as...
  • 68 篇 alibaba grp peop...
  • 66 篇 adobe research
  • 65 篇 national laborat...
  • 64 篇 peking univ peop...
  • 61 篇 univ oxford oxfo...
  • 59 篇 peng cheng labor...

作者

  • 80 篇 van gool luc
  • 71 篇 timofte radu
  • 65 篇 zhang lei
  • 43 篇 luc van gool
  • 40 篇 yang yi
  • 37 篇 loy chen change
  • 34 篇 li stan z.
  • 33 篇 liu yang
  • 33 篇 xiaoou tang
  • 33 篇 murino vittorio
  • 33 篇 chen chen
  • 33 篇 qi tian
  • 33 篇 li fei-fei
  • 32 篇 tian qi
  • 32 篇 sun jian
  • 30 篇 ying shan
  • 30 篇 pascal fua
  • 29 篇 darrell trevor
  • 28 篇 li xin
  • 28 篇 hanqing lu

语言

  • 23,043 篇 英文
  • 171 篇 其他
  • 20 篇 中文
  • 5 篇 土耳其文
  • 2 篇 日文
检索条件"任意字段=IEEE/CVF Conference on Computer Vision and Pattern Recognition"
23241 条 记 录,以下是4861-4870 订阅
Stacked Deep Multi-Scale Hierarchical Network for Fast Bokeh Effect Rendering from a Single Image
Stacked Deep Multi-Scale Hierarchical Network for Fast Bokeh...
收藏 引用
ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Dutta, Saikat Das, Sourya Dipta Shah, Nisarg A. Tiwari, Anil Kumar IIT Madras Chennai Tamil Nadu India Jadavpur Univ Kolkata India IIT Jodhpur Jodhpur Rajasthan India
The Bokeh Effect is one of the most desirable effects in photography for rendering artistic and aesthetic photos. Usually, it requires a DSLR camera with different aperture and shutter settings and certain photography... 详细信息
来源: 评论
M3DSSD: Monocular 3D Single Stage Object Detector
M3DSSD: Monocular 3D Single Stage Object Detector
收藏 引用
ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Luo, Shujie Dai, Hang Shao, Ling Ding, Yong Zhejiang Univ Coll Informat Sci & Elect Engn Hangzhou Peoples R China Zhejiang Univ Sch Micronano Elect Hangzhou Peoples R China Mohamed Bin Zayed Univ Artificial Intelligence Abu Dhabi U Arab Emirates Incept Inst Artificial Intelligence Abu Dhabi U Arab Emirates
In this paper, we propose a Monocular 3D Single Stage object Detector (M3DSSD) with feature alignment and asymmetric non-local attention. Current anchor-based monocular 3D object detection methods suffer from feature ... 详细信息
来源: 评论
Towards Extremely Compact RNNs for Video recognition with Fully Decomposed Hierarchical Tucker Structure
Towards Extremely Compact RNNs for Video Recognition with Fu...
收藏 引用
ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Yin, Miao Liao, Siyu Liu, Xiao-Yang Wang, Xiaodong Yuan, Bo Rutgers State Univ Newark NJ 07101 USA Amazon Seattle WA USA Columbia Univ New York NY 10027 USA
Recurrent Neural Networks (RNNs) have been widely used in sequence analysis and modeling. However, when processing high-dimensional data, RNNs typically require very large model sizes, thereby bringing a series of dep... 详细信息
来源: 评论
A Closer Look at Self-training for Zero-Label Semantic Segmentation
A Closer Look at Self-training for Zero-Label Semantic Segme...
收藏 引用
ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Pastore, Giuseppe Cermelli, Fabio Xian, Yongqin Mancini, Massimiliano Akata, Zeynep Caputo, Barbara Politecn Torino Turin Italy Italian Inst Technol Genoa Italy MPI Informat Saarbrucken Germany Univ Tubingen Tubingen Germany MPI Intelligent Syst Saarbrucken Germany
Being able to segment unseen classes not observed during training is an important technical challenge in deep learning, because of its potential to reduce the expensive annotation required for semantic segmentation. P... 详细信息
来源: 评论
LFNAT 2023 Challenge on Light Field Depth Estimation: Methods and Results
LFNAT 2023 Challenge on Light Field Depth Estimation: Method...
收藏 引用
2023 ieee/cvf conference on computer vision and pattern recognition Workshops, CVPRW 2023
作者: Sheng, Hao Liu, Yebin Yu, Jingyi Wu, Gaochang Xiong, Wei Guo, Longzhao Xie, Yanlin Zhang, Shuo Chang, Song Lin, Youfang Chao, Wentao Wang, Xuechun Wang, Guanghui Duan, Fuqing Wang, Tun Yang, Da Cui, Zhenglong Wang, Sizhe Zhao, Mingyuan Wang, Qiong Chen, Qianyu Liang, Zhengyu Wang, Yingqian Yang, Jungang Yang, Xueting Deng, Junli Cong, Ruixuan Chen, Rongshan State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University China Beihang Hangzhou Innovation Institute Yuhang China Faculty of Applied Sciences Macao Polytechnic University China Tsinghua University China Shanghaitech University China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University China Beijing Meet Yuan Co. Ltd China Beijing Key Laboratory of Traffic Data Analysis and Mining School of Computer and Information Technology Beijing Jiaotong University China Beijing Normal University China Toronto Metropolitan University Canada College of Computer Science and Technology Zhejiang University of Technology China National University of Defense Technology China School of Information and Communication Engineering Communication University of China China
This paper reviews the 1st LFNAT challenge on light field depth estimation, which aims at predicting disparity information of central view image in a light field (i.e., pixel offset between central view image and adja... 详细信息
来源: 评论
LAFEAT: Piercing Through Adversarial Defenses with Latent Features
LAFEAT: Piercing Through Adversarial Defenses with Latent Fe...
收藏 引用
ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Yu, Yunrui Gao, Xitong Xu, Cheng-Zhong Univ Macau Macau Sar Peoples R China Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen Peoples R China
Deep convolutional neural networks are susceptible to adversarial attacks. They can be easily deceived to give an incorrect output by adding a tiny perturbation to the input. This presents a great challenge in making ... 详细信息
来源: 评论
Difficulty Estimation with Action Scores for computer vision Tasks
Difficulty Estimation with Action Scores for Computer Vision...
收藏 引用
ieee computer Society conference on computer vision and pattern recognition Workshops (CVPRW)
作者: Octavio Arriaga Sebastian Palacio Matias Valdenegro-Toro University of Bremen German Research Center for Artificial Intelligence University of Groningen
As more machine learning models are now being applied in real world scenarios it has become crucial to evaluate their difficulties and biases. In this paper we present an unsupervised method for calculating a difficul...
来源: 评论
ECKPN: Explicit Class Knowledge Propagation Network for Transductive Few-shot Learning
ECKPN: Explicit Class Knowledge Propagation Network for Tran...
收藏 引用
ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Chen, Chaofan Yang, Xiaoshan Xu, Changsheng Huang, Xuhui Ma, Zhe Univ Sci & Technol China USTC Sch Informat Sci & Technol Hefei Anhui Peoples R China Chinese Acad Sci CASIA Inst Automat Natl Lab Pattern Recognit NLPR Beijing Peoples R China Univ Chinese Acad Sci UCAS Sch Artificial Intelligence Beijing Peoples R China Second Acad CASIC X Lab Beijing Peoples R China
Recently, the transductive graph-based methods have achieved great success in the few-shot classification task. However, most existing methods ignore exploring the class-level knowledge that can be easily learned by h... 详细信息
来源: 评论
Combining Semantic Guidance and Deep Reinforcement Learning For Generating Human Level Paintings
Combining Semantic Guidance and Deep Reinforcement Learning ...
收藏 引用
ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Singh, Jaskirat Zheng, Liang Australian Natl Univ Canberra ACT Australia
Generation of stroke-based non-photorealistic imagery, is an important problem in the computer vision community. As an endeavor in this direction, substantial recent research efforts have been focused on teaching mach... 详细信息
来源: 评论
Generalized Foggy-Scene Semantic Segmentation by Frequency Decoupling
Generalized Foggy-Scene Semantic Segmentation by Frequency D...
收藏 引用
ieee computer Society conference on computer vision and pattern recognition Workshops (CVPRW)
作者: Qi Bi Shaodi You Theo Gevers Computer Vision Research Group University of Amsterdam Amsterdam The Netherlands
Foggy-scene semantic segmentation (FSSS) is highly challenging due to the diverse effects of fog on scene properties and the limited training data. Existing research has mainly focused on domain adaptation for FSSS, w... 详细信息
来源: 评论