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

11,745 篇 会议
8 篇 期刊文献

馆藏范围

11,753 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

8,139 篇 工学
- 7,674 篇 计算机科学与技术...
- 804 篇 机械工程
- 580 篇 软件工程
- 376 篇 电气工程
- 252 篇 控制科学与工程
- 208 篇 光学工程
- 85 篇 生物工程
- 83 篇 信息与通信工程
- 29 篇 生物医学工程（可授...
- 23 篇 电子科学与技术（可...
- 21 篇 化学工程与技术
- 15 篇 交通运输工程
- 14 篇 安全科学与工程
- 10 篇 网络空间安全
- 8 篇 仪器科学与技术
- 6 篇 材料科学与工程（可...
- 6 篇 动力工程及工程热...
3,194 篇 医学
- 3,190 篇 临床医学
- 11 篇 基础医学(可授医学...
- 7 篇 公共卫生与预防医...
481 篇 理学
- 216 篇 物理学
- 203 篇 系统科学
- 88 篇 生物学
- 55 篇 数学
- 29 篇 统计学（可授理学、...
- 24 篇 化学
55 篇 管理学
- 29 篇 图书情报与档案管...
- 28 篇 管理科学与工程(可...
- 12 篇 工商管理
17 篇 法学
- 15 篇 社会学
6 篇 农学
4 篇 教育学
2 篇 经济学
1 篇 军事学
1 篇 艺术学

主题

5,434 篇 computer vision
2,516 篇 training
2,087 篇 pattern recognit...
1,621 篇 computational mo...
1,435 篇 visualization
1,306 篇 three-dimensiona...
1,060 篇 semantics
981 篇 codes
968 篇 benchmark testin...
898 篇 computer archite...
884 篇 deep learning
762 篇 task analysis
681 篇 feature extracti...
536 篇 face recognition
527 篇 conferences
515 篇 transformers
515 篇 neural networks
479 篇 object detection
466 篇 image segmentati...
454 篇 cameras

机构

168 篇 univ sci & techn...
144 篇 univ chinese aca...
144 篇 tsinghua univ pe...
143 篇 carnegie mellon ...
135 篇 chinese univ hon...
112 篇 peng cheng lab p...
108 篇 zhejiang univ pe...
97 篇 swiss fed inst t...
92 篇 tsinghua univers...
92 篇 sensetime res pe...
88 篇 shanghai ai lab ...
85 篇 zhejiang univers...
84 篇 shanghai jiao to...
78 篇 peng cheng labor...
77 篇 university of sc...
77 篇 alibaba grp peop...
76 篇 univ hong kong p...
76 篇 tech univ munich...
76 篇 stanford univ st...
73 篇 university of ch...

作者

76 篇 timofte radu
64 篇 van gool luc
50 篇 zhang lei
44 篇 yang yi
40 篇 loy chen change
34 篇 tao dacheng
32 篇 liu yang
32 篇 chen chen
30 篇 zhou jie
30 篇 tian qi
30 篇 sun jian
28 篇 zha zheng-jun
27 篇 qi tian
26 篇 li xin
26 篇 vasconcelos nuno
26 篇 ying shan
25 篇 liu xiaoming
25 篇 luc van gool
25 篇 boxin shi
24 篇 zheng wei-shi

语言

11,746 篇 英文
7 篇 其他

检索条件"任意字段=2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023"

共 11753 条记录，以下是4561-4570 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：

ANR: Articulated Neural Rendering for Virtual Avatars

ANR: Articulated Neural Rendering for Virtual Avatars

引用

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

作者： Raj, Amit Tanke, Julian Hays, James Vo, Minh Stoll, Carsten Lassner, Christoph Georgia Tech Atlanta GA 30332 USA Univ Bonn Bonn Germany Facebook Real Labs Redmond WA USA Epic Games Potomac MA USA

ISBN: (纸本)9781665445092

The combination of traditional rendering with neural networks in Deferred Neural Rendering (DNR) [38] provides a compelling balance between computational complexity and realism of the resulting images. Using skinned meshes for rendering articulating objects is a natural extension for the DNR framework and would open it up to a plethora of applications. However, in this case the neural shading step must account for deformations that are possibly not captured in the mesh, as well as alignment inaccuracies and dynamics-which can confound the DNR pipeline. We present Articulated Neural Rendering (ANR), a novel framework based on DNR which explicitly addresses its limitations for virtual human avatars. We show the superiority of ANR not only with respect to DNR but also with methods specialized for avatar creation and animation. In two user studies, we observe a clear preference for our avatar model and we demonstrate state-of-the-art performance on quantitative evaluation metrics. Perceptually, we observe better temporal stability, level of detail and plausibility. More results are available at our project page: https : // anr-avatars. ***.

关键词： Measurement computer vision Avatars Computational modeling Pipelines Neural networks Rendering (computer graphics)

来源：评论

学校读者我要写书评

暂无评论

Learning Multi-Scale Photo Exposure Correction

Learning Multi-Scale Photo Exposure Correction

引用

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

作者： Afifi, Mahmoud Derpanis, Konstantinos G. Ommer, Bjoern Brown, Michael S. Samsung AI Ctr SAIC Toronto ON Canada York Univ N York ON Canada Heidelberg Univ Heidelberg Germany

ISBN: (纸本)9781665445092

Capturing photographs with wrong exposures remains a major source of errors in camera-based imaging. Exposure problems are categorized as either: (i) overexposed, where the camera exposure was too long, resulting in bright and washed-out image regions, or (ii) underexposed, where the exposure was too short, resulting in dark regions. Both under- and overexposure greatly reduce the contrast and visual appeal of an image. Prior work mainly focuses on underexposed images or general image enhancement. In contrast, our proposed method targets both over- and underexposure errors in photographs. We formulate the exposure correction problem as two main sub-problems: (i) color enhancement and (ii) detail enhancement. Accordingly, we propose a coarse-to-fine deep neural network (DNN) model, trainable in an end-to-end manner, that addresses each subproblem separately. A key aspect of our solution is a new dataset of over 24,000 images exhibiting the broadest range of exposure values to date with a corresponding properly exposed image. Our method achieves results on par with existing state-of-the-art methods on underexposed images and yields significant improvements for images suffering from overexposure errors.

关键词： Deep learning Visualization computer vision Image color analysis Cameras pattern recognition Image enhancement

来源：评论

学校读者我要写书评

暂无评论

Single Image Depth Prediction with Wavelet Decomposition

Single Image Depth Prediction with Wavelet Decomposition

引用

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

作者： Ramamonjisoa, Michael Firman, Michael Watson, Jamie Lepetit, Vincent Turmukhambetov, Daniyar Univ Gustave Eiffel CNRS Ecole Ponts IMAGINELIGM Champs Sur Marne Marne La Vallee France Niantic San Francisco CA USA

ISBN: (纸本)9781665445092

We present a novel method for predicting accurate depths from monocular images with high efficiency. This optimal efficiency is achieved by exploiting wavelet decomposition, which is integrated in a fully differentiable encoder-decoder architecture. We demonstrate that we can reconstruct high-fidelity depth maps by predicting sparse wavelet coefficients. In contrast with previous works, we show that wavelet coefficients can be learned without direct supervision on coefficients. Instead we supervise only the final depth image that is reconstructed through the inverse wavelet transform. We additionally show that wavelet coefficients can be learned in fully self-supervised scenarios, without access to ground-truth depth. Finally, we apply our method to different state-of-the-art monocular depth estimation models, in each case giving similar or better results compared to the original model, while requiring less than half the multiplyadds in the decoder network.

关键词： Analytical models Neural networks Estimation computer architecture Wavelet analysis Decoding pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Hierarchical Motion Understanding via Motion Programs

Hierarchical Motion Understanding via Motion Programs

引用

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

作者： Kulal, Sumith Mao, Jiayuan Aiken, Alex Wu, Jiajun Stanford Univ Stanford CA 94305 USA MIT Cambridge MA 02139 USA

ISBN: (纸本)9781665445092

Current approaches to video analysis of human motion focus on raw pixels or keypoints as the basic units of reasoning. We posit that adding higher-level motion primitives, which can capture natural coarser units of motion such as "backswing" or "follow-through", can be used to improve downstream analysis tasks. This higher level of abstraction can also capture key features, such as loops of repeated primitives, that are currently inaccessible at lower levels of representation. We therefore introduce Motion Programs, a neuro-symbolic, program-like representation that expresses motions as a composition of high-level primitives. We also present a system for automatically inducing motion programs from videos of human motion and for leveraging motion programs in video synthesis. Experiments show that motion programs can accurately describe a diverse set of human motions and the inferred programs contain semantically meaningful motion primitives, such as arm swings and jumping jacks. Our representation also benefits downstream tasks such as video interpolation and video prediction and outperforms off-the-shelf models. We further demonstrate how these programs can detect diverse kinds of repetitive motion and facilitate interactive video editing.

关键词： Interpolation computer vision Computational modeling Predictive models Cognition pattern recognition Task analysis

来源：评论

学校读者我要写书评

暂无评论

StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation

StyleSpace Analysis: Disentangled Controls for StyleGAN Imag...

引用

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

作者： Wu, Zongze Lischinski, Dani Shechtman, Eli Hebrew Univ Jerusalem Jerusalem Israel Adobe Res San Jose CA USA

ISBN: (纸本)9781665445092

We explore and analyze the latent style space of StyleGAN2, a state-of-the-art architecture for image generation, using models pretrained on several different datasets. We first show that StyleSpace, the space of channel-wise style parameters, is significantly more disentangled than the other intermediate latent spaces explored by previous works. Next, we describe a method for discovering a large collection of style channels, each of which is shown to control a distinct visual attribute in a highly localized and disentangled manner. Third, we propose a simple method for identifying style channels that control a specific attribute, using a pretrained classifier or a small number of example images. Manipulation of visual attributes via these StyleSpace controls is shown to be better disentangled than via those proposed in previous works. To show this, we make use of a newly proposed Attribute Dependency metric. Finally, we demonstrate the applicability of StyleSpace controls to the manipulation of real images. Our findings pave the way to semantically meaningful and well-disentangled image manipulations via simple and intuitive interfaces.

关键词： Measurement Visualization computer vision Analytical models Image synthesis computer architecture Aerospace electronics

来源：评论

学校读者我要写书评

暂无评论

Efficient Object Embedding for Spliced Image Retrieval

Efficient Object Embedding for Spliced Image Retrieval

引用

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

作者： Chen, Bor-Chun Wu, Zuxuan Davis, Larry S. Lim, Ser-Nam Univ Maryland College Pk MD 20742 USA Facebook AI Menlo Pk CA 94025 USA Fudan Univ Shanghai Peoples R China

ISBN: (纸本)9781665445092

Detecting spliced images is one of the emerging challenges in computer vision. Unlike prior methods that focus on detecting low-level artifacts generated during the manipulation process, we use an image retrieval approach to tackle this problem. When given a spliced query image, our goal is to retrieve the original image from a database of authentic images. To achieve this goal, we propose representing an image by its constituent objects based on the intuition that the finest granularity of manipulations is often-times at the object-level. We introduce a framework, object embeddings for spliced image retrieval (OE-SIR), that utilizes modern object detectors to localize object regions. Each region is then embedded and collectively used to represent the image. Further, we propose a student-teacher training paradigm for learning discriminative embeddings within object regions to avoid expensive multiple forward passes. Detailed analysis of the efficacy of different feature embedding models is also provided in this study. Extensive experimental results show that the OE-SIR achieves state-of-the-art performance in spliced image retrieval.

关键词： Training Analytical models computer vision Databases Computational modeling Image retrieval Detectors

来源：评论

学校读者我要写书评

暂无评论

DART: Diversify-Aggregate-Repeat Training Improves Generalization of Neural Networks

DART: Diversify-Aggregate-Repeat Training Improves Generaliz...

引用

conference on computer vision and pattern recognition (cvpr)

作者： Samyak Jain Sravanti Addepalli Pawan Kumar Sahu Priyam Dey R. Venkatesh Babu Vision and AI Lab Indian Institute of Science Bangalore Indian Institute of Technology Varanasi Indian Institute of Technology Dhanbad

Generalization of Neural Networks is crucial for deploying them safely in the real world. Common training strategies to improve generalization involve the use of data augmentations, ensembling and model averaging. In this work, we first establish a surprisingly simple but strong benchmark for generalization which utilizes diverse augmentations within a training minibatch, and show that this can learn a more balanced distribution of features. Further, we propose Diversify-Aggregate-Repeat Training (DART) strategy that first trains diverse models using different augmentations (or domains) to explore the loss basin, and further Aggregates their weights to combine their expertise and obtain improved generalization. We find that Repeating the step of Aggregation throughout training improves the over-all optimization trajectory and also ensures that the individual models have sufficiently low loss barrier to obtain improved generalization on combining them. We theoretically justify the proposed approach and show that it indeed generalizes better. In addition to improvements in In-Domain generalization, we demonstrate SOTA performance on the Domain Generalization benchmarks in the popular DomainBed framework as well. Our method is generic and can easily be integrated with several base training algorithms to achieve performance gains. Our code is available here: https://***/val-iisc/DART.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Reciprocal Landmark Detection and Tracking with Extremely Few Annotations

Reciprocal Landmark Detection and Tracking with Extremely Fe...

引用

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

作者： Lin, Jianzhe Sahebzamani, Ghazal Luong, Christina Dezaki, Fatemeh Taheri Jafari, Mohammad Abolmaesumi, Purang Tsang, Teresa Univ British Columbia Dept Elect & Comp Engn Vancouver BC Canada Vancouver Gen Hosp Vancouver BC Canada Univ British Columbia Dept Med Vancouver BC Canada Univ British Columbia Div Cardiol Vancouver BC Canada

ISBN: (纸本)9781665445092

Localization of anatomical landmarks to perform two-dimensional measurements in echocardiography is part of routine clinical workflow in cardiac disease diagnosis. Automatic localization of those landmarks is highly desirable to improve workflow and reduce interobserver variability. Training a machine learning framework to perform such localization is hindered given the sparse nature of gold standard labels;only few percent of cardiac cine series frames are normally manually labeled for clinical use. In this paper, we propose a new end-to-end reciprocal detection and tracking model that is specifically designed to handle the sparse nature of echocardiography labels. The model is trained using few annotated frames across the entire cardiac cine sequence to generate consistent detection and tracking of landmarks, and an adversarial training for the model is proposed to take advantage of these annotated frames. The superiority of the proposed reciprocal model is demonstrated using a series of experiments.

关键词： Training Location awareness computer vision Echocardiography Annotations Computational modeling Machine learning

来源：评论

学校读者我要写书评

暂无评论

Differentiable SLAM-net: Learning Particle SLAM for Visual Navigation

Differentiable SLAM-net: Learning Particle SLAM for Visual N...

引用

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

作者： Karkus, Peter Cai, Shaojun Hsu, David Natl Univ Singapore Singapore Singapore

ISBN: (纸本)9781665445092

Simultaneous localization and mapping (SLAM) remains challenging for a number of downstream applications, such as visual robot navigation, because of rapid turns, featureless walls, and poor camera quality. We introduce the Differentiable SLAM Network (SLAM-net) along with a navigation architecture to enable planar robot navigation in previously unseen indoor environments. SLAM-net encodes a particle filter based SLAM algorithm in a differentiable computation graph, and learns task-oriented neural network components by backpropagating through the SLAM algorithm. Because it can optimize all model components jointly for the end-objective, SLAM-net learns to be robust in challenging conditions. We run experiments in the Habitat platform with different real-world RGB and RGB-D datasets. SLAM-net significantly outperforms the widely adapted ORB-SLAM in noisy conditions. Our navigation architecture with SLAMnet improves the state-of-the-art for the Habitat Challenge 2020 PointNav task by a large margin (37% to 64% success).

关键词： Visualization Simultaneous localization and mapping Navigation Robot vision systems Neural networks computer architecture Particle filters

来源：评论

学校读者我要写书评

暂无评论

Learning Event Guided High Dynamic Range Video Reconstruction

Learning Event Guided High Dynamic Range Video Reconstructio...

引用

conference on computer vision and pattern recognition (cvpr)

作者： Yixin Yang Jin Han Jinxiu Liang Imari Sato Boxin Shi National Key Laboratory for Multimedia Information Processing School of Computer Science Peking University National Engineering Research Center of Visual Technology School of Computer Science Peking University Graduate School of Information Science and Technology The University of Tokyo National Institute of Informatics

Limited by the trade-off between frame rate and exposure time when capturing moving scenes with conventional cameras, frame based HDR video reconstruction suffers from scene-dependent exposure ratio balancing and ghosting artifacts. Event cameras provide an alternative visual representation with a much higher dynamic range and temporal resolution free from the above issues, which could be an effective guidance for HDR imaging from LDR videos. In this paper, we propose a multimodal learning framework for event guided HDR video reconstruction. In order to better leverage the knowledge of the same scene from the two modalities of visual signals, a multimodal representation alignment strategy to learn a shared latent space and a fusion module tailored to complementing two types of signals for different dynamic ranges in different regions are proposed. Temporal correlations are utilized recurrently to suppress the flickering effects in the reconstructed HDR video. The proposed HDRev-Net demonstrates state-of-the-art performance quantitatively and qualitatively for both synthetic and real-world data.

关键词：

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 << < 453 454 455 456 457 458 459 460 461 462 > >>

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：