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31-40 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：

Single-Shot Freestyle Dance Reenactment

Single-Shot Freestyle Dance Reenactment

引用

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

作者： Gafni, Oran Ashual, Oron Wolf, Lior Facebook AI Res Menlo Pk CA 94025 USA Tel Aviv Univ Tel Aviv Israel

ISBN: (纸本)9781665445092

The task of motion transfer between a source dancer and a target person is a special case of the pose transfer problem, in which the target person changes their pose in accordance with the motions of the dancer. In this work, we propose a novel method that can reanimate a single image by arbitrary video sequences, unseen during training. The method combines three networks: (i) a segmentation-mapping network, (ii) a realistic frame-rendering network, and (iii) a face refinement network. By separating this task into three stages, we are able to attain a novel sequence of realistic frames, capturing natural motion and appearance. Our method obtains significantly better visual quality than previous methods and is able to animate diverse body types and appearances, which are captured in challenging poses.

关键词： Training Visualization Image segmentation computer vision Motion segmentation Face recognition Biological system modeling

来源：评论

学校读者我要写书评

暂无评论

Topological Planning with Transformers for vision-and-Language Navigation

Topological Planning with Transformers for Vision-and-Langua...

引用

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

作者： Chen, Kevin Chen, Junshen K. Chuang, Jo Vazquez, Marynel Savarese, Silvio Stanford Univ Stanford CA 94305 USA Yale Univ New Haven CT 06520 USA

ISBN: (纸本)9781665445092

Conventional approaches to vision-and-language navigation (VLN) are trained end-to-end but struggle to perform well in freely traversable environments. Inspired by the robotics community, we propose a modular approach to VLN using topological maps. Given a natural language instruction and topological map, our approach leverages attention mechanisms to predict a navigation plan in the map. The plan is then executed with low-level actions (e.g. FORWARD, ROTATE) using a robust controller. Experiments show that our method outperforms previous end-to-end approaches, generates interpretable navigation plans, and exhibits intelligent behaviors such as backtracking.

关键词： computer vision Backtracking Navigation Natural languages Buildings Transformers Planning

来源：评论

学校读者我要写书评

暂无评论

SMURF: Self-Teaching Multi-Frame Unsupervised RAFT with Full-Image Warping

SMURF: Self-Teaching Multi-Frame Unsupervised RAFT with Full...

引用

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

作者： Stone, Austin Maurer, Daniel Ayvaci, Alper Angelova, Anelia Jonschkowski, Rico Google Robot Mountain View CA 94043 USA Waymo Mountain View CA USA

ISBN: (纸本)9781665445092

We present SMURF, a method for unsupervised learning of optical flow that improves state of the art on all benchmarks by 36% to 40% (over the prior best method UFlow) and even outperforms several supervised approaches such as PWC-Net and FlowNet2. Our method integrates architecture improvements from supervised optical flow, i.e. the RAFT model, with new ideas for unsupervised learning that include a sequence-aware self-supervision loss, a technique for handling out-of-frame motion, and an approach for learning effectively from multi-frame video data while still only requiring two frames for inference.

关键词： Optical losses computer vision Computational modeling Estimation computer architecture Benchmark testing Data models

来源：评论

学校读者我要写书评

暂无评论

NewtonianVAE: Proportional Control and Goal Identification from Pixels via Physical Latent Spaces

NewtonianVAE: Proportional Control and Goal Identification f...

引用

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

作者： Jaques, Miguel Burke, Michael Hospedales, Timothy Univ Edinburgh Edinburgh Midlothian Scotland Monash Univ Melbourne Vic Australia

ISBN: (纸本)9781665445092

Learning low-dimensional latent state space dynamics models has proven powerful for enabling vision-based planning and learning for control. We introduce a latent dynamics learning framework that is uniquely designed to induce proportional controlability in the latent space, thus enabling the use of simple and well-known PID controllers. We show that our learned dynamics model enables proportional control from pixels, dramatically simplifies and accelerates behavioural cloning of vision-based controllers, and provides interpretable goal discovery when applied to imitation learning of switching controllers from demonstration. Notably, such proportional controlability also allows for robust path following from visual demonstrations using Dynamic Movement Primitives in the learned latent space.

关键词： Visualization computer vision Proportional control Cloning Switches Aerospace electronics Planning

来源：评论

学校读者我要写书评

暂无评论

Learning Semantic-Aware Dynamics for Video Prediction

Learning Semantic-Aware Dynamics for Video Prediction

引用

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

作者： Bei, Xinzhu Yang, Yanchao Soatto, Stefano Univ Calif Los Angeles Vis Lab Los Angeles CA 90024 USA Stanford Univ Stanford CA 94305 USA

ISBN: (纸本)9781665445092

We propose an architecture and training scheme to predict video frames by explicitly modeling dis-occlusions and capturing the evolution of semantically consistent regions in the video. The scene layout (semantic map) and motion (optical flow) are decomposed into layers, which are predicted and fused with their context to generate future layouts and motions. The appearance of the scene is warped from past frames using the predicted motion in co-visible regions;dis-occluded regions are synthesized with content-aware inpainting utilizing the predicted scene layout. The result is a predictive model that explicitly represents objects and learns their class-specific motion, which we evaluate on video prediction benchmarks.

关键词： Training computer vision Layout Semantics Dynamics computer architecture Predictive models

来源：评论

学校读者我要写书评

暂无评论

Domain-Independent Dominance of Adaptive Methods

Domain-Independent Dominance of Adaptive Methods

引用

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

作者： Savarese, Pedro McAllester, David Babu, Sudarshan Maire, Michael TTI Chicago Chicago IL 60637 USA Univ Chicago Chicago IL 60637 USA

ISBN: (纸本)9781665445092

From a simplified analysis of adaptive methods, we derive AvaGrad, a new optimizer which outperforms SGD on vision tasks when its adaptability is properly tuned. We observe that the power of our method is partially explained by a decoupling of learning rate and adaptability, greatly simplifying hyperparameter search. In light of this observation, we demonstrate that, against conventional wisdom, Adam can also outperform SGD on vision tasks, as long as the coupling between its learning rate and adaptability is taken into account. In practice, AvaGrad matches the best results, as measured by generalization accuracy, delivered by any existing optimizer (SGD or adaptive) across image classification (CIFAR, ImageNet) and character-level language modelling (Penn Treebank) tasks. When training GANs, AvaGrad improves upon existing optimizers.

关键词： Training Couplings computer vision Stochastic processes Tools pattern recognition Task analysis

来源：评论

学校读者我要写书评

暂无评论

Recognizing Actions in Videos from Unseen Viewpoints

Recognizing Actions in Videos from Unseen Viewpoints

引用

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

作者： Piergiovanni, A. J. Ryoo, Michael S. Indiana Univ Bloomington IN 47405 USA SUNY Stony Brook Stony Brook NY 11794 USA

ISBN: (纸本)9781665445092

Standard methods for video recognition use large CNNs designed to capture spatio-temporal data. However;training these models requires a large amount of labeled training data, containing a wide variety of actions, scenes, settings and camera viewpoints. In this paper, we show that current convolutional neural network models are unable to recognize actions from camera viewpoints not present in their training data (i.e., unseen view action recognition). To address this, we develop approaches based on 3D representations and introduce a new geometric convolutional layer that can learn viewpoint invariant representations. Further, we introduce a new, challenging dataset for unseen view recognition and show the approaches ability to learn viewpoint invariant representations.

关键词： Training computer vision Three-dimensional displays Training data Cameras Data models pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Multiple Instance Captioning: Learning Representations from Histopathology Textbooks and Articles

Multiple Instance Captioning: Learning Representations from ...

引用

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

作者： Gamper, Jevgenij Rajpoot, Nasir Univ Warwick Coventry W Midlands England

ISBN: (纸本)9781665445092

We present ARCH, a computational pathology (CP) multiple instance captioning dataset to facilitate dense supervision of CP tasks. Existing CP datasets focus on narrow tasks;ARCH on the other hand contains dense diagnostic and morphological descriptions for a range of stains, tissue types and pathologies. Using intrinsic dimensionality estimation, we show that ARCH is the only CP dataset to (ARCH-)rival its computer vision analog MS-COCO Captions. We conjecture that an encoder pre-trained on dense image captions learns transferable representations for most CP tasks. We support the conjecture with evidence that ARCH representation transfers to a variety of pathology sub-tasks better than ImageNet features or representations obtained via self-supervised or multi-task learning on pathology images alone. We release our best model and invite other researchers to test it on their CP tasks.

关键词： computer vision Histopathology Computational modeling Estimation pattern recognition Task analysis

来源：评论

学校读者我要写书评

暂无评论

Minimally Invasive Surgery for Sparse Neural Networks in Contrastive Manner

Minimally Invasive Surgery for Sparse Neural Networks in Con...

引用

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

作者： Yu, Chong NVIDIA Beijing Peoples R China Fudan Univ Shanghai Peoples R China

ISBN: (纸本)9781665445092

With the development of deep learning, neural networks tend to be deeper and larger to achieve good performance. Trained models are more compute-intensive and memory-intensive, which lead to the big challenges on memory bandwidth, storage, latency, and throughput. In this paper, we propose the neural network compression method named minimally invasive surgery. Different from traditional model compression and knowledge distillation methods, the proposed method refers to the minimally invasive surgery principle. It learns the principal features from a pair of dense and compressed models in a contrastive manner. It also optimizes the neural networks to meet the specific hardware acceleration requirements. Through qualitative, quantitative, and ablation experiments, the proposed method shows a compelling performance, acceleration, and generalization in various tasks.

关键词： Knowledge engineering Minimally invasive surgery Computational modeling Throughput Probability distribution pattern recognition Task analysis

来源：评论

学校读者我要写书评

暂无评论

Differentiable Patch Selection for Image recognition

Differentiable Patch Selection for Image Recognition

引用

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

作者： Cordonnier, Jean-Baptiste Mahendran, Aravindh Dosovitskiy, Alexey Weissenborn, Dirk Uszkoreit, Jakob Unterthiner, Thomas Ecole Polytech Fed Lausanne Lausanne Switzerland Google Res Brain Team Mountain View CA USA

ISBN: (纸本)9781665445092

Neural Networks require large amounts of memory and compute to process high resolution images, even when only a small part of the image is actually informative for the task at hand. We propose a method based on a differentiable Top-K operator to select the most relevant parts of the input to efficiently process high resolution images. Our method may be interfaced with any downstream neural network, is able to aggregate information from different patches in a flexible way, and allows the whole model to be trained end-to-end using backpropagation. We show results for traffic sign recognition, inter-patch relationship reasoning, and fine-grained recognition without using object/part bounding box annotations during training.

关键词： Training computer vision Image resolution Image recognition Computational modeling Neural networks Memory management

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 << < 1 2 3 4 5 6 7 8 9 10 > >>

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：