检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

19,438 篇 会议
46 篇 期刊文献
5 册 图书

馆藏范围

19,488 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

12,440 篇 工学
- 10,282 篇 计算机科学与技术...
- 2,395 篇 机械工程
- 2,007 篇 软件工程
- 813 篇 光学工程
- 531 篇 电气工程
- 419 篇 控制科学与工程
- 322 篇 信息与通信工程
- 210 篇 测绘科学与技术
- 80 篇 生物医学工程（可授...
- 73 篇 电子科学与技术（可...
- 70 篇 生物工程
- 60 篇 仪器科学与技术
- 38 篇 建筑学
- 36 篇 土木工程
- 33 篇 力学（可授工学、理...
- 31 篇 航空宇航科学与技...
- 26 篇 安全科学与工程
- 20 篇 材料科学与工程（可...
- 20 篇 交通运输工程
3,409 篇 医学
- 3,408 篇 临床医学
1,980 篇 理学
- 1,006 篇 数学
- 973 篇 物理学
- 359 篇 统计学（可授理学、...
- 336 篇 生物学
- 231 篇 系统科学
- 24 篇 化学
258 篇 管理学
- 138 篇 管理科学与工程(可...
- 122 篇 图书情报与档案管...
- 27 篇 工商管理
19 篇 法学
- 19 篇 社会学
14 篇 农学
8 篇 教育学
7 篇 经济学
3 篇 军事学
3 篇 艺术学

主题

7,893 篇 computer vision
2,727 篇 training
2,680 篇 pattern recognit...
1,760 篇 computational mo...
1,644 篇 visualization
1,410 篇 cameras
1,372 篇 three-dimensiona...
1,327 篇 shape
1,213 篇 face recognition
1,207 篇 image segmentati...
1,164 篇 feature extracti...
1,109 篇 robustness
1,087 篇 semantics
983 篇 layout
959 篇 object detection
949 篇 computer archite...
942 篇 benchmark testin...
931 篇 codes
902 篇 computer science
859 篇 deep learning

机构

174 篇 univ sci & techn...
161 篇 carnegie mellon ...
148 篇 univ chinese aca...
144 篇 chinese univ hon...
110 篇 microsoft resear...
106 篇 tsinghua univ pe...
103 篇 zhejiang univ pe...
99 篇 swiss fed inst t...
92 篇 tsinghua univers...
89 篇 microsoft res as...
88 篇 shanghai ai lab ...
81 篇 zhejiang univers...
76 篇 alibaba grp peop...
73 篇 university of sc...
73 篇 hong kong univ s...
72 篇 peking univ peop...
72 篇 university of ch...
68 篇 shanghai jiao to...
66 篇 univ oxford oxfo...
66 篇 shanghai jiao to...

作者

79 篇 van gool luc
70 篇 zhang lei
59 篇 timofte radu
48 篇 yang yi
47 篇 xiaoou tang
45 篇 luc van gool
43 篇 darrell trevor
43 篇 tian qi
42 篇 loy chen change
42 篇 sun jian
42 篇 li fei-fei
40 篇 qi tian
38 篇 li stan z.
36 篇 chen xilin
36 篇 torralba antonio
35 篇 vasconcelos nuno
35 篇 shan shiguang
35 篇 liu yang
34 篇 liu xiaoming
34 篇 tao dacheng

语言

19,484 篇 英文
2 篇 日文
2 篇 中文
1 篇 其他

检索条件"任意字段=IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2000"

共 19489 条记录，以下是4971-4980 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Deep Visual Geo-localization Benchmark

Deep Visual Geo-localization Benchmark

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Berton, Gabriele Mereu, Riccardo Trivigno, Gabriele Masone, Carlo Csurka, Gabriela Sattler, Torsten Caputo, Barbara Politecn Torino Turin Italy CINI Turin Italy NAVER LABS Europe Meylan France Czech Tech Univ CIIRC Prague Czech Republic

ISBN: (数字)9781665469463

ISBN: (纸本)9781665469463

In this paper, we propose a new open-source benchmarking framework for Visual Geo-localization (VG) that allows to build, train, and test a wide range of commonly used architectures, with the flexibility to change individual components of a geo-localization pipeline. The purpose of this framework is twofold: i) gaining insights into how different components and design choices in a VG pipeline impact the final results, both in terms of performance (recall@N metric) and system requirements (such as execution time and memory consumption);ii) establish a systematic evaluation protocol for comparing different methods. Using the proposed framework, we perform a large suite of experiments which provide criteria for choosing backbone, aggregation and negative mining depending on the use-case and requirements. We also assess the impact of engineering techniques like pre/post-processing, data augmentation and image resizing, showing that better performance can be obtained through somewhat simple procedures: for example, downscaling the images' resolution to 80% can lead to similar results with a 36% savings in extraction time and dataset storage requirement. Code and trained models are available at dataset storage requirement. https://deep-vg- ***/.

关键词： Measurement Visualization computer vision Protocols Image resolution Computational modeling Pipelines

来源：评论

学校读者我要写书评

暂无评论

High-Fidelity Neural Human Motion Transfer from Monocular Video

High-Fidelity Neural Human Motion Transfer from Monocular Vi...

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Kappel, Moritz Golyanik, Vladislav Elgharib, Mohamed Henningson, Jann-Ole Seidel, Hans-Peter Castillo, Susana Theobalt, Christian Magnor, Marcus TU Braunschweig Comp Graph Lab Braunschweig Germany Max Planck Inst Informat Saarland Informat Campus Saarbrucken Germany

ISBN: (纸本)9781665445092

Video-based human motion transfer creates video animations of humans following a source motion. Current methods show remarkable results for tightly-clad subjects. However, the lack of temporally consistent handling of plausible clothing dynamics, including fine and high-frequency details, significantly limits the attainable visual quality. We address these limitations for the first time in the literature and present a new framework which performs high-fidelity and temporally-consistent human motion transfer with natural pose-dependent non-rigid deformations, for several types of loose garments. In contrast to the previous techniques, we perform image generation in three subsequent stages: synthesizing human shape, structure, and appearance. Given a monocular RGB video of an actor, we train a stack of recurrent deep neural networks that generate these intermediate representations from 2D poses and their temporal derivatives. Splitting the difficult motion transfer problem into subtasks that are aware of the temporal motion context helps us to synthesize results with plausible dynamics and pose-dependent detail. It also allows artistic control of results by manipulation of individual framework stages. In the experimental results, we significantly outperform the state-of-the-art in terms of video realism.

关键词： Deep learning Visualization computer vision Codes Shape Image synthesis Clothing

来源：评论

学校读者我要写书评

暂无评论

TCTS: A Task-Consistent Two-stage Framework for Person Search

TCTS: A Task-Consistent Two-stage Framework for Person Searc...

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Wang, Cheng Ma, Bingpeng Chang, Hong Shan, Shiguang Chen, Xilin Univ Chinese Acad Sci Beijing 100049 Peoples R China Chinese Acad Sci Inst Comp Technol Key Lab Intelligent Informat Proc Beijing 100190 Peoples R China Peng Cheng Lab Shenzhen 518055 Peoples R China

ISBN: (纸本)9781728171685

The state of the art person search methods separate person search into detection and re-ID stages, but ignore the consistency between these two stages. The general person detector has no special attention on the query target;The re-ID model is trained on hand-drawn bounding boxes which are not available in person search. To address the consistency problem, we introduce a Task-Consist Two-Stage (TCTS) person search framework, includes an identity-guided query (IDGQ) detector and a Detection Results Adapted (DRA) re-ID model. In the detection stage, the IDGQ detector learns an auxiliary identity branch to compute query similarity scores for proposals. With consideration of the query similarity scores and foreground score, IDGQ produces query-like bounding boxes for the re-ID stage. In the re-ID stage, we predict identity labels of detected bounding boxes, and use these examples to construct a more practical mixed train set for the DRA model. Training on the mixed train set improves the robustness of the reID stage to inaccurate detection. We evaluate our method on two benchmark datasets, CUHK-SYSU and PRW. Our framework achieves 93.9% of mAP and 95.1% of rank1 accuracy on CUHK-SYSU, outperforming the previous state of the art methods.

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

A Fully Automatic Method to Extract the Heart Rate from Thermal Video

A Fully Automatic Method to Extract the Heart Rate from Ther...

引用

26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Gault, Travis R. Farag, Aly A. Univ Louisville Louisville KY 40292 USA

ISBN: (纸本)9780769549903

This work deals with non-invasive and non-intrusive measurements of the human facial vasculature from thermal IR to measure cardiovascular vital signs. A robust, fully automatic measurement system is developed to study infrared videos of 32 under three imaging scenarios. Vascular mapping, blood perfusion modeling, and wavelet analysis are used to calculate heart rate from 512 video frames in near real time. Multiple measurement locations are considered to analyze accuracy and sensitivity in a novel approach, revealing that the 60% of vessel segments in the forehead region are capable of producing 85% accuracy of measurement or better.

关键词： biomedical optical imaging cardiovascular system face recognition haemorheology infrared imaging medical image processing video streaming wavelet transforms

来源：评论

学校读者我要写书评

暂无评论

PEM: Prototype-based Efficient MaskFormer for Image Segmentation

PEM: Prototype-based Efficient MaskFormer for Image Segmenta...

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Cavagnero, Niccolo Rosi, Gabriele Cuttano, Claudia Pistilli, Francesca Ciccone, Marco Averta, Giuseppe Cermelli, Fabio Politecn Torino Turin Italy Focoos AI Rome Italy

ISBN: (纸本)9798350353006

Recent transformer-based architectures have shown impressive results in the field of image segmentation. Thanks to their flexibility, they obtain outstanding performance in multiple segmentation tasks, such as semantic and panoptic, under a single unified framework. To achieve such impressive performance, these architectures employ intensive operations and require substantial computational resources, which are often not available, especially on edge devices. To fill this gap, we propose Prototype-based Efficient MaskFormer (PEM), an efficient transformer-based architecture that can operate in multiple segmentation tasks. PEM proposes a novel prototype-based cross-attention which leverages the redundancy of visual features to restrict the computation and improve the efficiency without harming the performance. In addition, PEM introduces an efficient multi-scale feature pyramid network, capable of extracting features that have high semantic content in an efficient way, thanks to the combination of deformable convolutions and context-based self-modulation. We benchmark the proposed PEM architecture on two tasks, semantic and panoptic segmentation, evaluated on two different datasets, Cityscapes and ADE20K. PEM demonstrates outstanding performance on every task and dataset, outperforming task-specific architectures while being comparable and even better than computationally expensive baselines. Code is available at https://***/NiccoloCavagnero/PEM.

关键词： computer vision Efficient Neural Network Image Segmentation

来源：评论

学校读者我要写书评

暂无评论

UniRepLKNet: A Universal Perception Large-Kernel ConvNet for Audio, Video, Point Cloud, Time-Series and Image recognition

UniRepLKNet: A Universal Perception Large-Kernel ConvNet for...

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Ding, Xiaohan Zhang, Yiyuan Ge, Yixiao Zhao, Sijie Song, Lin Yue, Xiangyu Shan, Ying Tencent AI Lab Shenzhen Peoples R China Chinese Univ Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9798350353013;9798350353006

Large-kernel convolutional neural networks (ConvNets) have recently received extensive research attention, but two unresolved and critical issues demand further investigation. 1) The architectures of existing large-kernel ConvNets largely follow the design principles of conventional ConvNets or transformers, while the architectural design for large-kernel ConvNets remains under-addressed. 2) As transformers have dominated multiple modalities, it remains to be investigated whether ConvNets also have a strong universal perception ability in domains beyond vision. In this paper, we contribute from two aspects. 1) We propose four architectural guidelines for designing large-kernel ConvNets, the core of which is to exploit the essential characteristics of large kernels that distinguish them from small kernels - they can see wide without going deep. Following such guidelines, our proposed large-kernel ConvNet shows leading performance in image recognition (ImageNet accuracy of 88.0%, ADE20K mIoU of 55.6%, and COCO box AP of 56.4%), demonstrating better performance and higher speed than the recent powerful competitors. 2) We discover large kernels are the key to unlocking the exceptional performance of ConvNets in domains where they were originally not proficient. With certain modality-related pre-processing approaches, the proposed model achieves state-of-the-art performance on time-series forecasting and audio recognition tasks even without modality-specific customization to the architecture. All the code and models are publicly available on GitHub and Huggingface.

关键词： Large-Kernel ConvNets Multimodal Learning Network Architecture

来源：评论

学校读者我要写书评

暂无评论

Space-Time Distillation for Video Super-Resolution

Space-Time Distillation for Video Super-Resolution

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Xiao, Zeyu Fu, Xueyang Huang, Jie Cheng, Zhen Xiong, Zhiwei Univ Sci & Technol China Hefei Anhui Peoples R China

ISBN: (纸本)9781665445092

Compact video super-resolution (VSR) networks can be easily deployed on resource-limited devices, e.g., smartphones and wearable devices, but have considerable performance gaps compared with complicated VSR networks that require a large amount of computing resources. In this paper, we aim to improve the performance of compact VSR networks without changing their original architectures, through a knowledge distillation approach that transfers knowledge from a complicated VSR network to a compact one. Specifically, we propose a space-time distillation (STD) scheme to exploit both spatial and temporal knowledge in the VSR task. For space distillation, we extract spatial attention maps that hint the high-frequency video content from both networks, which are further used for transferring spatial modeling capabilities. For time distillation, we narrow the performance gap between compact models and complicated models by distilling the feature similarity of the temporal memory cells, which are encoded from the sequence of feature maps generated in the training clips using ConvLSTM. During the training process, STD can be easily incorporated into any network without changing the original network architecture. Experimental results on standard benchmarks demonstrate that, in resource-constrained situations, the proposed method notably improves the performance of existing VSR networks without increasing the inference time.

关键词： Training Performance evaluation Knowledge engineering Wearable computers Superresolution Network architecture pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Stochastic Variance Reduced Ensemble Adversarial Attack for Boosting the Adversarial Transferability

Stochastic Variance Reduced Ensemble Adversarial Attack for ...

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Xiong, Yifeng Lin, Jiadong Zhang, Min Hopcroft, John E. He, Kun Huazhong Univ Sci & Technol Dept Comp Sci Wuhan Peoples R China Cornell Univ Dept Comp Sci Ithaca NY 14853 USA

ISBN: (数字)9781665469463

ISBN: (纸本)9781665469463

The black-box adversarial attack has attracted impressive attention for its practical use in the field of deep learning security. Meanwhile, it is very challenging as there is no access to the network architecture or internal weights of the target model. Based on the hypothesis that if an example remains adversarial for multiple models, then it is more likely to transfer the attack capability to other models, the ensemble-based adversarial attack methods are efficient and widely used for black-box attacks. However, ways of ensemble attack are rather less investigated, and existing ensemble attacks simply fuse the outputs of all the models evenly. In this work, we treat the iterative ensemble attack as a stochastic gradient descent optimization process, in which the variance of the gradients on different models may lead to poor local optima. To this end, we propose a novel attack method called the stochastic variance reduced ensemble (SVRE) attack, which could reduce the gradient variance of the ensemble models and take full advantage of the ensemble attack. Empirical results on the standard ImageNet dataset demonstrate that the proposed method could boost the adversarial transferability and outperforms existing ensemble attacks significantly. Code is available at https://***/JHL-HUST/SVRE.

关键词： Deep learning Fuses Stochastic processes Network architecture Boosting pattern recognition Security

来源：评论

学校读者我要写书评

暂无评论

LMGP: Lifted Multicut Meets Geometry Projections for Multi-Camera Multi-Ooject Tracking

LMGP: Lifted Multicut Meets Geometry Projections for Multi-C...

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Nguyen, Duy M. H. Henschel, Roberto Rosenhahn, Bodo Sonntag, Daniel Swoboda, Paul Max Planck Inst Informat Saarland Informat Campus Saarbrucken Germany Leibniz Univ Hannover Inst Informat Proc Hannover Germany Oldenburg Univ Oldenburg Germany German Res Ctr Artificial Intelligence Saarbrucken Germany

ISBN: (数字)9781665469463

ISBN: (纸本)9781665469463

Multi-Camera Multi-Object Tracking is currently drawing attention in the computer vision field due to its superior performance in real-world applications such as video surveillance with crowded scenes or in wide spaces. In this work, we propose a mathematically elegant multi-camera multiple object tracking approach based on a spatial-temporal lifted multicut formulation. Our model utilizes state-of-the-art tracklets produced by single-camera trackers as proposals. As these tracklets may contain ID-Switch errors, we refine them through a novel pre-clustering obtained from 3D geometry projections. As a result, we derive a better tracking graph without ID switches and more precise affinity costs for the data association phase. Tracklets are then matched to multi-camera trajectories by solving a global lifted multicut formulation that incorporates short and long-range temporal interactions on tracklets located in the same camera as well as inter-camera ones. Experimental results on the WildTrack dataset yield near perfect performance, outperforming state-of-the-art trackers on Campus while being on par on the PETS-09 dataset. We will release our implementations at this link https://***/nhmduy/LMGP.

关键词： Geometry Training computer vision Three-dimensional displays Video surveillance Mathematical models Trajectory

来源：评论

学校读者我要写书评

暂无评论

Unsupervised Person Re-identification via Softened Similarity Learning

Unsupervised Person Re-identification via Softened Similarit...

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Lin, Yutian Xie, Lingxi Wu, Yu Yan, Chenggang Tian, Qi Hangzhou Dianzi Univ Hangzhou Zhejiang Peoples R China Huawei Inc Shenzhen Peoples R China Baidu Res Beijing Peoples R China Univ Technol Sydney ReLER Reler NSW Australia Huawei Noahs Ark Lab Shenzhen Peoples R China

ISBN: (纸本)9781728171685

Person re-identification (re-ID) is an important topic in computer vision. This paper studies the unsupervised setting of re-ID, which does not require any labeled information and thus is freely deployed to new scenarios. There are very few studies under this setting, and one of the best approach till now used iterative clustering and classification, so that unlabeled images are clustered into pseudo classes for a classifier to get trained, and the updated features are used for clustering and so on. This approach suffers two problems, namely, the difficulty of determining the number of clusters, and the hard quantization loss in clustering. In this paper, we follow the iterative training mechanism but discard clustering, since it incurs loss from hard quantization, yet its only product, image-level similarity, can be easily replaced by pairwise computation and a softened classification task. With these improvements, our approach becomes more elegant and is more robust to hyper-parameter changes. Experiments on two image-based and video-based datasets demonstrate state-of-the-art performance under the unsupervised re-ID setting.

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共500页 << < 491 492 493 494 495 496 497 498 499 500 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：