咨询与建议

限定检索结果

文献类型

  • 8,901 篇 会议
  • 43 篇 期刊文献
  • 18 册 图书

馆藏范围

  • 8,961 篇 电子文献
  • 1 种 纸本馆藏

日期分布

学科分类号

  • 4,560 篇 工学
    • 4,020 篇 计算机科学与技术...
    • 2,178 篇 软件工程
    • 1,241 篇 光学工程
    • 555 篇 控制科学与工程
    • 431 篇 信息与通信工程
    • 430 篇 机械工程
    • 294 篇 电气工程
    • 287 篇 仪器科学与技术
    • 179 篇 生物工程
    • 159 篇 生物医学工程(可授...
    • 119 篇 电子科学与技术(可...
    • 61 篇 安全科学与工程
    • 58 篇 建筑学
    • 58 篇 化学工程与技术
    • 52 篇 土木工程
    • 49 篇 交通运输工程
    • 40 篇 力学(可授工学、理...
  • 2,065 篇 理学
    • 1,382 篇 物理学
    • 1,198 篇 数学
    • 420 篇 统计学(可授理学、...
    • 238 篇 生物学
    • 54 篇 化学
    • 36 篇 系统科学
  • 263 篇 管理学
    • 180 篇 图书情报与档案管...
    • 89 篇 管理科学与工程(可...
    • 47 篇 工商管理
  • 223 篇 医学
    • 222 篇 临床医学
    • 39 篇 基础医学(可授医学...
  • 205 篇 艺术学
    • 205 篇 设计学(可授艺术学...
  • 45 篇 法学
    • 43 篇 社会学
  • 21 篇 农学
  • 14 篇 教育学
  • 9 篇 经济学
  • 6 篇 军事学

主题

  • 3,412 篇 computer vision
  • 1,216 篇 pattern recognit...
  • 946 篇 cameras
  • 908 篇 conferences
  • 765 篇 computer science
  • 674 篇 image segmentati...
  • 618 篇 layout
  • 598 篇 training
  • 548 篇 shape
  • 518 篇 robustness
  • 451 篇 feature extracti...
  • 448 篇 humans
  • 445 篇 face recognition
  • 405 篇 computational mo...
  • 402 篇 object detection
  • 365 篇 visualization
  • 356 篇 computer archite...
  • 336 篇 application soft...
  • 304 篇 lighting
  • 259 篇 image reconstruc...

机构

  • 41 篇 microsoft resear...
  • 30 篇 department of co...
  • 25 篇 department of co...
  • 23 篇 institute for co...
  • 22 篇 department of co...
  • 22 篇 school of comput...
  • 20 篇 university of sc...
  • 20 篇 swiss fed inst t...
  • 19 篇 tsinghua univers...
  • 19 篇 institute of com...
  • 18 篇 swiss fed inst t...
  • 17 篇 the robotics ins...
  • 17 篇 carnegie mellon ...
  • 17 篇 computer vision ...
  • 17 篇 department of co...
  • 16 篇 institute of inf...
  • 16 篇 school of comput...
  • 15 篇 school of comput...
  • 15 篇 carnegie mellon ...
  • 14 篇 national laborat...

作者

  • 57 篇 timofte radu
  • 25 篇 huang thomas s.
  • 24 篇 van gool luc
  • 23 篇 s.k. nayar
  • 22 篇 nayar shree k.
  • 22 篇 t. kanade
  • 21 篇 jain anil k.
  • 20 篇 luc van gool
  • 19 篇 t.s. huang
  • 18 篇 xiaoou tang
  • 18 篇 murino vittorio
  • 18 篇 horst bischof
  • 17 篇 a.k. jain
  • 17 篇 t. darrell
  • 16 篇 g. healey
  • 16 篇 bowyer kevin w.
  • 16 篇 bischof horst
  • 15 篇 m.j. black
  • 15 篇 li stan z.
  • 15 篇 m. shah

语言

  • 8,932 篇 英文
  • 21 篇 其他
  • 8 篇 中文
  • 1 篇 土耳其文
检索条件"任意字段=IEEE-Computer-Society Conference on Computer Vision and Pattern Recognition Workshops"
8962 条 记 录,以下是401-410 订阅
排序:
VFHQ: A High-Quality Dataset and Benchmark for Video Face Super-Resolution
VFHQ: A High-Quality Dataset and Benchmark for Video Face Su...
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Xie, Liangbin Wang, Xintao Zhang, Honglun Dong, Chao Shan, Ying Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen Key Lab Comp Vis & Pattern Recognit Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Tencent PCG ARC Lab Shenzhen Peoples R China
Most of the existing video face super-resolution (VFSR) methods are trained and evaluated on VoxCeleb1, which is designed specifically for speaker identification and the frames in this dataset are of low quality. As a... 详细信息
来源: 评论
Pseudo-label Generation for Agricultural Robotics Applications
Pseudo-label Generation for Agricultural Robotics Applicatio...
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Ciarfuglia, Thomas A. Motoi, Ionut Marian Saraceni, Leonardo Nardi, Daniele Sapienza Univ Rome Dept Comp Sci Management & Automat Engn DIAG Rome Italy
In the context of table grape cultivation there is rising interest in robotic solutions for harvesting, pruning, precision spraying and other agronomic tasks. Perception algorithms at the core of these systems require... 详细信息
来源: 评论
Tragedy Plus Time: Capturing Unintended Human Activities from Weakly-labeled Videos
Tragedy Plus Time: Capturing Unintended Human Activities fro...
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Chakravarthy, Arnav Fang, Zhiyuan Yang, Yezhou Arizona State Univ Tempe AZ 85287 USA
In videos that contain actions performed unintentionally, agents do not achieve their desired goals. In such videos, it is challenging for computer vision systems to understand high-level concepts such as goal-directe... 详细信息
来源: 评论
deepPIC: Deep Perceptual Image Clustering For Identifying Bias In vision Datasets
deepPIC: Deep Perceptual Image Clustering For Identifying Bi...
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Jaipuria, Nikita Stevo, Katherine Zhang, Xianling Gaopande, Meghana L. Garcia, Ian Calle Jain, Jinesh Murali, Vidya N. Ford Greenfield Labs Palo Alto CA 94304 USA Georgia Inst Technol Atlanta GA 30332 USA
Dataset bias in manually collected datasets is a known problem in computer vision. In safety-critical applications such as autonomous driving, these biases can lead to catastrophic errors from models trained on such d... 详细信息
来源: 评论
Few-Shot Image Classification Along Sparse Graphs
Few-Shot Image Classification Along Sparse Graphs
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Comer, Joseph F. Jacobson, Philip L. Hoffmann, Heiko HRL Labs LLC 3011 Malibu Canyon Rd Malibu CA 90265 USA
Few-shot learning remains a challenging problem, with unsatisfactory 1-shot accuracies for most real-world data. Here, we present a new perspective for data distributions in the feature space of a deep network and sho... 详细信息
来源: 评论
Blind Non-Uniform Motion Deblurring using Atrous Spatial Pyramid Deformable Convolution and Deblurring-Reblurring Consistency
Blind Non-Uniform Motion Deblurring using Atrous Spatial Pyr...
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Huo, Dong Masoumzadeh, Abbas Yang, Yee-Hong Univ Alberta Dept Comp Sci Edmonton AB Canada
Many deep learning based methods are designed to remove non-uniform (spatially variant) motion blur caused by object motion and camera shake without knowing the blur kernel. Some methods directly output the latent sha... 详细信息
来源: 评论
What Should Be Equivariant In Self-Supervised Learning
What Should Be Equivariant In Self-Supervised Learning
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Xie, Yuyang Wen, Jianhong Lau, Kin Wai Rehman, Yasar Abbas Ur Shen, Jiajun TCL AI Lab Hong Kong Peoples R China Fuzhou Univ Fuzhou Peoples R China City Univ Hong Kong Hong Kong Peoples R China
Self-supervised learning (SSL) aims to learn feature representation without human-annotated data. Existing methods approach this goal by encouraging the feature representations to be invariant under a set of task-irre... 详细信息
来源: 评论
Interpolation-Based Event Visual Data Filtering Algorithms
Interpolation-Based Event Visual Data Filtering Algorithms
收藏 引用
2023 ieee/CVF conference on computer vision and pattern recognition workshops, CVPRW 2023
作者: Kowalczyk, Marcin Kryjak, Tomasz AGH University of Krakow Embedded Vision Systems Group Poland
The field of neuromorphic vision is developing rapidly, and event cameras are finding their way into more and more applications. However, the data stream from these sensors is characterised by significant noise. In th... 详细信息
来源: 评论
Learning to Ask Informative Sub-Questions for Visual Question Answering
Learning to Ask Informative Sub-Questions for Visual Questio...
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Uehara, Kohei Duan, Nan Harada, Tatsuya Univ Tokyo Tokyo Japan Microsoft Res Asia Beijing Peoples R China Univ Tokyo RIKEN Tokyo Japan
VQA (Visual Question Answering) model tends to make incorrect inferences for questions that require reasoning over world knowledge. Recent study has shown that training VQA models with questions that provide lower-lev... 详细信息
来源: 评论
Does Federated Dropout actually work?
Does Federated Dropout actually work?
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Cheng, Gary Charles, Zachary Garrett, Zachary Rush, Keith Stanford Univ Stanford CA 94305 USA Google Res Mountain View CA USA
Model sizes are limited in Federated Learning due to network bandwidth and on-device memory constraints. The success of increasing model sizes in other machine learning domains motivates the development of methods for... 详细信息
来源: 评论