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

11,414 篇 会议
9 篇 期刊文献

馆藏范围

11,423 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

7,979 篇 工学
- 7,533 篇 计算机科学与技术...
- 805 篇 机械工程
- 401 篇 电气工程
- 390 篇 软件工程
- 231 篇 控制科学与工程
- 58 篇 光学工程
- 42 篇 生物工程
- 37 篇 信息与通信工程
- 19 篇 生物医学工程（可授...
- 14 篇 电子科学与技术（可...
- 13 篇 化学工程与技术
- 9 篇 安全科学与工程
- 7 篇 交通运输工程
- 6 篇 仪器科学与技术
- 4 篇 土木工程
- 3 篇 轻工技术与工程
3,137 篇 医学
- 3,137 篇 临床医学
- 8 篇 基础医学(可授医学...
- 5 篇 药学(可授医学、理...
- 4 篇 公共卫生与预防医...
307 篇 理学
- 200 篇 系统科学
- 63 篇 物理学
- 43 篇 生物学
- 30 篇 数学
- 15 篇 统计学（可授理学、...
- 14 篇 化学
29 篇 管理学
- 17 篇 图书情报与档案管...
- 13 篇 管理科学与工程(可...
- 5 篇 工商管理
3 篇 法学
- 3 篇 社会学
2 篇 教育学
2 篇 农学
1 篇 经济学
1 篇 艺术学

主题

5,612 篇 computer vision
2,584 篇 training
2,092 篇 pattern recognit...
1,682 篇 computational mo...
1,496 篇 visualization
1,343 篇 three-dimensiona...
1,098 篇 semantics
1,007 篇 benchmark testin...
1,005 篇 codes
927 篇 computer archite...
898 篇 deep learning
790 篇 task analysis
708 篇 feature extracti...
571 篇 conferences
563 篇 face recognition
520 篇 transformers
517 篇 neural networks
493 篇 object detection
476 篇 image segmentati...
452 篇 cameras

机构

172 篇 univ sci & techn...
150 篇 univ chinese aca...
148 篇 tsinghua univ pe...
145 篇 carnegie mellon ...
136 篇 chinese univ hon...
116 篇 peng cheng lab p...
106 篇 zhejiang univ pe...
97 篇 swiss fed inst t...
96 篇 sensetime res pe...
95 篇 tsinghua univers...
91 篇 shanghai ai lab ...
85 篇 shanghai jiao to...
83 篇 alibaba grp peop...
81 篇 peng cheng labor...
80 篇 zhejiang univers...
80 篇 stanford univ st...
78 篇 univ hong kong p...
77 篇 university of ch...
75 篇 australian natl ...
75 篇 tech univ munich...

作者

64 篇 timofte radu
60 篇 van gool luc
50 篇 zhang lei
44 篇 yang yi
39 篇 tao dacheng
35 篇 loy chen change
32 篇 tian qi
31 篇 zhou jie
31 篇 sun jian
30 篇 liu yang
29 篇 vasconcelos nuno
29 篇 qi tian
29 篇 zha zheng-jun
28 篇 chen chen
27 篇 boxin shi
26 篇 li xin
26 篇 luc van gool
26 篇 pollefeys marc
25 篇 liu xiaoming
25 篇 ying shan

语言

11,420 篇 英文
3 篇 其他

检索条件"任意字段=2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2021"

共 11423 条记录，以下是231-240 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：

SceneGen: Learning to Generate Realistic Traffic Scenes

SceneGen: Learning to Generate Realistic Traffic Scenes

引用

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

作者： Tan, Shuhan Wong, Kelvin Wang, Shenlong Manivasagam, Sivabalan Ren, Mengye Urtasun, Raquel Uber Adv Technol Grp Beijing Peoples R China Sun Yat Sen Univ Guangzhou Peoples R China Univ Toronto Toronto ON Canada

ISBN: (纸本)9781665445092

We consider the problem of generating realistic traffic scenes automatically. Existing methods typically insert actors into the scene according to a set of hand-crafted heuristics and are limited in their ability to model the true complexity and diversity of real traffic scenes, thus inducing a content gap between synthesized traffic scenes versus real ones. As a result, existing simulators lack the fidelity necessary to train and test self-driving vehicles. To address this limitation, we present SceneGen-a neural autoregressive model of traffic scenes that eschews the need for rules and heuristics. In particular, given the ego-vehicle state and a high definition map of surrounding area, SceneGen inserts actors of various classes into the scene and synthesizes their sizes, orientations, and velocities. We demonstrate on two large-scale datasets SceneGen's ability to faithfully model distributions of real traffic scenes. Moreover, we show that SceneGen coupled with sensor simulation can be used to train perception models that generalize to the real world.

关键词： computer vision Computational modeling Complexity theory pattern recognition

来源：评论

学校读者我要写书评

暂无评论

View-Guided Point Cloud Completion

View-Guided Point Cloud Completion

引用

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

作者： Zhang, Xuancheng Feng, Yutong Li, Siqi Zou, Changqing Wan, Hai Zhao, Xibin Guo, Yandong Gao, Yue Tsinghua Univ Sch Software KLISS BNRist Beijing Peoples R China Tsinghua Univ THUICBS Beijing Peoples R China Huawei Technol Canada Co Ltd Markham ON Canada OPPO Res Inst Beijing Peoples R China

ISBN: (纸本)9781665445092

This paper presents a view-guided solution for the task of point cloud completion. Unlike most existing methods directly inferring the missing points using shape priors, we address this task by introducing ViPC (view-guided point cloud completion) that takes the missing crucial global structure information from an extra single-view image. By leveraging a framework that sequentially performs effective cross-modality and cross-level fusions, our method achieves significantly superior results over typical existing solutions on a new large-scale dataset we collect for the view-guided point cloud completion task.

关键词： computer vision Shape Sensor fusion pattern recognition Task analysis Image reconstruction Periodic structures

来源：评论

学校读者我要写书评

暂无评论

FlowStep3D: Model Unrolling for Self-Supervised Scene Flow Estimation

FlowStep3D: Model Unrolling for Self-Supervised Scene Flow E...

引用

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

作者： Kittenplon, Yair Eldar, Yonina C. Raviv, Dan Tel Aviv Univ Tel Aviv Israel Weizmann Inst Sci Rehovot Israel

ISBN: (纸本)9781665445092

Estimating the 3D motion of points in a scene, known as scene flow, is a core problem in computer vision. Traditional learning-based methods designed to learn end-to-end 3D flow often suffer from poor generalization. Here we present a recurrent architecture that learns a single step of an unrolled iterative alignment procedure for refining scene flow predictions. Inspired by classical algorithms, we demonstrate iterative convergence toward the solution using strong regularization. The proposed method can handle sizeable temporal deformations and suggests a slimmer architecture than competitive all-to-all correlation approaches. Trained on FlyingThings3D synthetic data only, our network successfully generalizes to real scans, outperforming all existing methods by a large margin on the KITTI self-supervised benchmark.(1)

关键词： Training Learning systems computer vision Three-dimensional displays Refining Estimation computer architecture

来源：评论

学校读者我要写书评

暂无评论

Pedestrian and Ego-vehicle Trajectory Prediction from Monocular Camera

Pedestrian and Ego-vehicle Trajectory Prediction from Monocu...

引用

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

作者： Neumann, Lukas Vedaldi, Andrea Czech Tech Univ Fac Elect Engn Visual Recognit Grp Prague Czech Republic Univ Oxford Dept Engn Sci Visual Geometry Grp Oxford England

ISBN: (纸本)9781665445092

Predicting future pedestrian trajectory is a crucial component of autonomous driving systems, as recognizing critical situations based only on current pedestrian position may come too late for any meaningful corrective action (e.g. breaking) to take place. In this paper, we propose a new method to predict future position of pedestrians, with respect to a predicted future position of the ego-vehicle, thus giving a assistive/autonomous driving system sufficient time to respond. The method explicitly disentangles actual movement of pedestrians in real world from the ego-motion of the vehicle, using a future pose prediction network trained in self-supervised fashion, which allows the method to observe and predict the intrinsic pedestrian motion in a normalised view, that captures the same real-world location across multiple frames. The method is evaluated on two public datasets, where it achieves state-of-the-art results in pedestrian trajectory prediction from an on-board camera.

关键词： Training computer vision Drives Cameras Trajectory pattern recognition Autonomous vehicles

来源：评论

学校读者我要写书评

暂无评论

Points as Queries: Weakly Semi-supervised Object Detection by Points

Points as Queries: Weakly Semi-supervised Object Detection b...

引用

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

作者： Chen, Liangyu Yang, Tong Zhang, Xiangyu Zhang, Wei Sun, Jian MEGVII Technol Beijing Peoples R China Fudan Univ Shanghai Peoples R China

ISBN: (纸本)9781665445092

We propose a novel point annotated setting for the weakly semi-supervised object detection task, in which the dataset comprises small fully annotated images and large weakly annotated images by points. It achieves a balance between tremendous annotation burden and detection performance. Based on this setting, we analyze existing detectors and find that these detectors have difficulty in fully exploiting the power of the annotated points. To solve this, we introduce a new detector, Point DETR, which extends DETR by adding a point encoder. Extensive experiments conducted on MS-COCO dataset in various data settings show the effectiveness of our method. In particular, when using 20% fully labeled data from COCO, our detector achieves a promising performance, 33.3 AP, which outperforms a strong baseline (FCOS) by 2.0 AP, and we demonstrate the point annotations bring over 10 points in various AR metrics.

关键词： Measurement computer vision Annotations Detectors Object detection pattern recognition Task analysis

来源：评论

学校读者我要写书评

暂无评论

Depth from Camera Motion and Object Detection

Depth from Camera Motion and Object Detection

引用

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

作者： Griffin, Brent A. Corso, Jason J. Univ Michigan Ann Arbor MI 48109 USA Stevens Inst Artificial Intelligence Hoboken NJ USA

ISBN: (纸本)9781665445092

This paper addresses the problem of learning to estimate the depth of detected objects given some measurement of camera motion (e.g., from robot kinematics or vehicle odometry). We achieve this by 1) designing a recurrent neural network (DBox) that estimates the depth of objects using a generalized representation of bounding boxes and uncalibrated camera movement and 2) introducing the Object Depth via Motion and Detection Dataset (ODMD). ODMD training data are extensible and configurable, and the ODMD benchmark includes 21,600 examples across four validation and test sets. These sets include mobile robot experiments using an end-effector camera to locate objects from the YCB dataset and examples with perturbations added to camera motion or bounding box data. In addition to the ODMD benchmark, we evaluate DBox in other monocular application domains, achieving state-of-the-art results on existing driving and robotics benchmarks and estimating the depth of objects using a camera phone.

关键词： Training Perturbation methods Robot kinematics Robot vision systems Training data Object detection Benchmark testing

来源：评论

学校读者我要写书评

暂无评论

Isometric Multi-Shape Matching

Isometric Multi-Shape Matching

引用

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

作者： Gao, Maolin Laehner, Zorah Thunberg, Johan Cremers, Daniel Bernard, Florian Tech Univ Munich Munich Germany Halmstad Univ Halmstad Sweden Univ Siegen Siegen Germany

ISBN: (纸本)9781665445092

Finding correspondences between shapes is a fundamental problem in computer vision and graphics, which is relevant for many applications, including 3D reconstruction, object tracking, and style transfer. The vast majority of correspondence methods aim to find a solution between pairs of shapes, even if multiple instances of the same class are available. While isometries are often studied in shape correspondence problems, they have not been considered explicitly in the multi-matching setting. This paper closes this gap by proposing a novel optimisation formulation for isometric multi-shape matching. We present a suitable optimisation algorithm for solving our formulation and provide a convergence and complexity analysis. Our algorithm obtains multi-matchings that are by construction provably cycle-consistent. We demonstrate the superior performance of our method on various datasets and set the new state-of-the-art in isometric multi-shape matching.

关键词： computer vision Three-dimensional displays Shape Linear programming Complexity theory Object tracking Optimization

来源：评论

学校读者我要写书评

暂无评论

DeepSurfels: Learning Online Appearance Fusion

DeepSurfels: Learning Online Appearance Fusion

引用

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

作者： Mihajlovic, Marko Weder, Silvan Pollefeys, Marc Oswald, Martin R. Swiss Fed Inst Technol Dept Comp Sci Zurich Switzerland Microsoft Mixed Real Zurich Switzerland AI Zurich Lab Zurich Switzerland

ISBN: (纸本)9781665445092

We present DeepSurfels, a novel hybrid scene representation for geometry and appearance information. DeepSurfels combines explicit and neural building blocks to jointly encode geometry and appearance information. In contrast to established representations, DeepSurfels better represents high-frequency textures, is well-suited for online updates of appearance information, and can be easily combined with machine learning methods. We further present an end-to-end trainable online appearance fusion pipeline that fuses information from RGB images into the proposed scene representation and is trained using self-supervision imposed by the reprojection error with respect to the input images. Our method compares favorably to classical texture mapping approaches as well as recent learning-based techniques. Moreover, we demonstrate lower runtime, improved generalization capabilities, and better scalability to larger scenes compared to existing methods.

关键词： Geometry Runtime Shape Scalability Pipelines Machine learning Rendering (computer graphics)

来源：评论

学校读者我要写书评

暂无评论

Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations

Continual Semantic Segmentation via Repulsion-Attraction of ...

引用

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

作者： Michieli, Umberto Zanuttigh, Pietro Univ Padua Dept Informat Engn Padua Italy

ISBN: (纸本)9781665445092

Deep neural networks suffer from the major limitation of catastrophic forgetting old tasks when learning new ones. In this paper we focus on class incremental continual learning in semantic segmentation, where new categories are made available over time while previous training data is not retained. The proposed continual learning scheme shapes the latent space to reduce forgetting whilst improving the recognition of novel classes. Our framework is driven by three novel components which we also combine on top of existing techniques effortlessly. First, prototypes matching enforces latent space consistency on old classes, constraining the encoder to produce similar latent representation for previously seen classes in the subsequent steps. Second, features sparsification allows to make room in the latent space to accommodate novel classes. Finally, contrastive learning is employed to cluster features according to their semantics while tearing apart those of different classes. Extensive evaluation on the Pascal VOC2012 and ADE20K datasets demonstrates the effectiveness of our approach, significantly outperforming state-of-the-art methods.

关键词： Deep learning computer vision Limiting Shape Semantics Prototypes Training data

来源：评论

学校读者我要写书评

暂无评论

Virtual Fully-Connected Layer: Training a Large-Scale Face recognition Dataset with Limited Computational Resources

Virtual Fully-Connected Layer: Training a Large-Scale Face R...

引用

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

作者： Li, Pengyu Wang, Biao Zhang, Lei Alibaba Grp Artificial Intelligence Ctr DAMO Acad Hangzhou Peoples R China Hong Kong Polytech Univ Dept Comp Hong Kong Peoples R China

ISBN: (纸本)9781665445092

Recently, deep face recognition has achieved significant progress because of Convolutional Neural Networks (CNNs) and large-scale datasets. However, training CNNs on a large-scale face recognition dataset with limited computational resources is still a challenge. This is because the classification paradigm needs to train a fully-connected layer as the category classifier, and its parameters will be in the hundreds of millions if the training dataset contains millions of identities. This requires many computational resources, such as GPU memory. The metric learning paradigm is an economical computation method, but its performance is greatly inferior to that of the classification paradigm. To address this challenge, we propose a simple but effective CNN layer called the Virtual fully-connected (Virtual FC) layer to reduce the computational consumption of the classification paradigm. Without bells and whistles, the proposed Virtual FC reduces the parameters by more than 100 times with respect to the fully-connected layer and achieves competitive performance on mainstream face recognition evaluation datasets. Moreover, the performance of our Virtual FC layer on the evaluation datasets is superior to that of the metric learning paradigm by a significant margin. Our code will be released in hopes of disseminating our idea to other domains1.

关键词： Training Measurement computer vision Codes Face recognition Memory management Graphics processing units

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 << < 20 21 22 23 24 25 26 27 28 29 > >>

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：