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

11,885 篇 会议
5 篇 期刊文献

馆藏范围

11,890 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

8,059 篇 工学
- 7,617 篇 计算机科学与技术...
- 796 篇 机械工程
- 688 篇 电气工程
- 360 篇 软件工程
- 228 篇 控制科学与工程
- 40 篇 光学工程
- 19 篇 生物工程
- 17 篇 信息与通信工程
- 12 篇 生物医学工程（可授...
- 6 篇 电子科学与技术（可...
- 6 篇 建筑学
- 6 篇 交通运输工程
- 5 篇 仪器科学与技术
- 5 篇 化学工程与技术
- 5 篇 安全科学与工程
- 4 篇 土木工程
3,347 篇 医学
- 3,346 篇 临床医学
- 4 篇 基础医学(可授医学...
- 4 篇 公共卫生与预防医...
253 篇 理学
- 198 篇 系统科学
- 32 篇 物理学
- 21 篇 生物学
- 18 篇 数学
- 9 篇 统计学（可授理学、...
- 7 篇 化学
17 篇 管理学
- 12 篇 管理科学与工程(可...
- 7 篇 图书情报与档案管...
- 5 篇 工商管理
3 篇 法学
- 3 篇 社会学
3 篇 教育学
- 3 篇 教育学
2 篇 农学
1 篇 经济学
1 篇 军事学

主题

5,633 篇 computer vision
2,668 篇 training
2,203 篇 pattern recognit...
1,747 篇 computational mo...
1,502 篇 visualization
1,360 篇 three-dimensiona...
1,074 篇 semantics
999 篇 benchmark testin...
986 篇 codes
959 篇 computer archite...
891 篇 deep learning
777 篇 conferences
754 篇 task analysis
700 篇 feature extracti...
561 篇 transformers
533 篇 face recognition
527 篇 neural networks
495 篇 object detection
490 篇 image segmentati...
468 篇 cameras

机构

174 篇 univ sci & techn...
145 篇 carnegie mellon ...
144 篇 univ chinese aca...
144 篇 tsinghua univ pe...
134 篇 chinese univ hon...
110 篇 zhejiang univ pe...
109 篇 peng cheng lab p...
99 篇 swiss fed inst t...
91 篇 tsinghua univers...
90 篇 shanghai ai lab ...
87 篇 sensetime res pe...
86 篇 shanghai jiao to...
83 篇 zhejiang univers...
82 篇 tech univ munich...
79 篇 university of sc...
79 篇 stanford univ st...
78 篇 univ hong kong p...
77 篇 australian natl ...
76 篇 alibaba grp peop...
75 篇 peng cheng labor...

作者

75 篇 timofte radu
64 篇 van gool luc
50 篇 zhang lei
43 篇 yang yi
37 篇 loy chen change
36 篇 tao dacheng
32 篇 zhou jie
31 篇 chen chen
30 篇 liu yang
30 篇 tian qi
29 篇 sun jian
29 篇 zha zheng-jun
28 篇 li xin
27 篇 qi tian
26 篇 vasconcelos nuno
25 篇 liu xiaoming
25 篇 darrell trevor
24 篇 zheng wei-shi
24 篇 luo ping
24 篇 ying shan

语言

11,863 篇 英文
26 篇 其他
1 篇 中文

检索条件"任意字段=2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2024"

共 11890 条记录，以下是261-270 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：

Unified-IO 2: Scaling Autoregressive Multimodal Models with vision, Language, Audio, and Action

Unified-IO 2: Scaling Autoregressive Multimodal Models with ...

引用

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

作者： Lu, Jiasen Clark, Christopher Lee, Sangho Zhang, Zichen Khosla, Savya Marten, Ryan Hoiem, Derek Kembhavi, Aniruddha Allen Inst AI Seattle WA 98103 USA Univ Illinois Urbana IL USA Univ Washington Seattle WA 98195 USA

ISBN: (纸本)9798350353006

We present UNIFIED-IO 2, the first autoregressive multimodal model that is capable of understanding and generating image, text, audio, and action. To unify different modalities, we tokenize inputs and outputs - images, text, audio, action, bounding boxes etc., into a shared semantic space and then process them with a single encoder-decoder transformer model. Since training with such diverse modalities is challenging, we propose various architectural improvements to stabilize model training. We train our model from scratch on a large multimodal pre-training corpus from diverse sources with a multimodal mixture of denoisers objective. To learn an expansive set of skills, such as following multimodal instructions, we construct and finetune on an ensemble of 120 datasets with prompts and augmentations. With a single unified model, UNIFIED-IO 2 achieves state-of-the-art performance on the GRIT benchmark and strong results in more than 35 benchmarks, including image generation and understanding, natural language understanding, video and audio understanding, and robotic manipulation. We release all our models to the research community.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

SHViT: Single-Head vision Transformer with Memory Efficient Macro Design

SHViT: Single-Head Vision Transformer with Memory Efficient ...

引用

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

作者： Yun, Seokju Ro, Youngmin Univ Seoul Machine Intelligence Lab Seoul South Korea

ISBN: (纸本)9798350353013;9798350353006

Recently, efficient vision Transformers have shown great performance with low latency on resource-constrained devices. Conventionally, they use 4x4 patch embeddings and a 4-stage structure at the macro level, while utilizing sophisticated attention with multi-head configuration at the micro level. This paper aims to address computational redundancy at all design levels in a memory-efficient manner. We discover that using larger-stride patchify stem not only reduces memory access costs but also achieves competitive performance by leveraging token representations with reduced spatial redundancy from the early stages. Furthermore, our preliminary analyses suggest that attention layers in the early stages can be substituted with convolutions, and several attention heads in the latter stages are computationally redundant. To handle this, we introduce a single-head attention module that inherently prevents head redundancy and simultaneously boosts accuracy by parallelly combining global and local information. Building upon our solutions, we introduce SHViT, a SingleHead vision Transformer that obtains the state-of-the-art speed-accuracy tradeoff. For example, on ImageNet-1k, our SHViT-S4 is 3.3x, 8.1x, and 2.4x faster than MobileViTv2 x1.0 on GPU, CPU, and iPhone12 mobile device, respectively, while being 1.3% more accurate. For object detection and instance segmentation on MS COCO using MaskRCNN head, our model achieves performance comparable to FastViT-SA12 while exhibiting 3.8x and 2.0x lower backbone latency on GPU and mobile device, respectively.

关键词： CNNs efficient visual backbone vision Transformer

来源：评论

学校读者我要写书评

暂无评论

Learning for Transductive Threshold Calibration in Open-World recognition

Learning for Transductive Threshold Calibration in Open-Worl...

引用

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

作者： Zhang, Qin An, Dongsheng Xiao, Tianjun He, Tong Tang, Qingming Wu, Ying Nian Tighe, Joseph Xing, Yifan AWS AI Labs Shanghai Peoples R China Amazon Web Serv Shanghai Peoples R China Alexa AI Seattle WA USA

ISBN: (纸本)9798350353006

In deep metric learning for visual recognition, the calibration of distance thresholds is crucial for achieving desired model performance in the true positive rates (TPR) or true negative rates (TNR). However, calibrating this threshold presents challenges in open-world scenarios, where the test classes can be entirely disjoint from those encountered during training. We define the problem of finding distance thresholds for a trained embedding model to achieve target performance metrics over unseen open-world test classes as open-world threshold calibration. Existing posthoc threshold calibration methods, reliant on inductive inference and requiring a calibration dataset with a similar distance distribution as the test data, often prove ineffective in open-world scenarios. To address this, we introduce OpenGCN, a Graph Neural Network-based transductive threshold calibration method with enhanced adaptability and robustness. OpenGCN learns to predict pairwise connectivity for the unlabeled test instances embedded in a graph to determine its TPR and TNR at various distance thresholds, allowing for transductive inference of the distance thresholds which also incorporates test-time information. Extensive experiments across open-world visual recognition benchmarks validate OpenGCN's superiority over existing posthoc calibration methods for open-world threshold calibration.

关键词： deep metric learning open world recognition Posthoc calibration

来源：评论

学校读者我要写书评

暂无评论

Differentiable Shadow Mapping for Efficient Inverse Graphics

Differentiable Shadow Mapping for Efficient Inverse Graphics

引用

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

作者： Worchel, Markus Alexa, Marc TU Berlin Berlin Germany

ISBN: (纸本)9798350301298

We show how shadows can be efficiently generated in differentiable rendering of triangle meshes. Our central observation is that pre-filtered shadow mapping, a technique for approximating shadows based on rendering from the perspective of a light, can be combined with existing differentiable rasterizers to yield differentiable visibility information. We demonstrate at several inverse graphics problems that differentiable shadow maps are orders of magnitude faster than differentiable light transport simulation with similar accuracy - while differentiable rasterization without shadows often fails to converge.

关键词： vision + graphics

来源：评论

学校读者我要写书评

暂无评论

An Iterative Quantum Approach for Transformation Estimation from Point Sets

An Iterative Quantum Approach for Transformation Estimation ...

引用

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

作者： Meli, Natacha Kuete Mannel, Florian Lellmann, Jan Univ Lubeck Inst Math & Image Comp Lubeck Germany

ISBN: (纸本)9781665469463

We propose an iterative method for estimating rigid transformations from point sets using adiabatic quantum computation. Compared to existing quantum approaches, our method relies on an adaptive scheme to solve the problem to high precision, and does not suffer from inconsistent rotation matrices. Experimentally, our method performs robustly on several 2D and 3D datasets even with high outlier ratio.

关键词： computer vision Three-dimensional displays Annealing Estimation Quantum annealing pattern recognition Iterative methods

来源：评论

学校读者我要写书评

暂无评论

Composing Object Relations and Attributes for Image-Text Matching

Composing Object Relations and Attributes for Image-Text Mat...

引用

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

作者： Pham, Khoi Huynh, Chuong Lim, Ser-Nam Shrivastava, Abhinav Univ Maryland College Pk MD 20742 USA Univ Cent Florida Orlando FL 32816 USA

ISBN: (纸本)9798350353006

We study the visual semantic embedding problem for image-text matching. Most existing work utilizes a tailored cross-attention mechanism to perform local alignment across the two image and text modalities. This is computationally expensive, even though it is more powerful than the unimodal dual-encoder approach. This work introduces a dual-encoder image-text matching model, leveraging a scene graph to represent captions with nodes for objects and attributes interconnected by relational edges. Utilizing a graph attention network, our model efficiently encodes object-attribute and object-object semantic relations, resulting in a robust and fast-performing system. Representing caption as a scene graph offers the ability to utilize the strong relational inductive bias of graph neural networks to learn object-attribute and object-object relations effectively. To train the model, we propose losses that align the image and caption both at the holistic level ( image-caption) and the local level (image-object entity), which we show is key to the success of the model. Our model is termed Composition model for Object Relations and Attributes, CORA. Experimental results on two prominent image-text retrieval benchmarks, Flickr30K and MS-COCO, demonstrate that CORA outperforms existing state-of-the-art computationally expensive cross-attention methods regarding recall score while achieving fast computation speed of the dual encoder. Our code is available at https://***/vkhoi/cora_cvpr24

关键词： image retrieval image-text matching vision-language

来源：评论

学校读者我要写书评

暂无评论

CPR-Coach: Recognizing Composite Error Actions based on Single-class Training

CPR-Coach: Recognizing Composite Error Actions based on Sing...

引用

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

作者： Wang, Shunli Wang, Shuaibing Yang, Dingkang Li, Mingcheng Kuang, Haopeng Zhao, Xiao Su, Liuzhen Zhai, Peng Zhang, Lihua Fudan Univ Acad Engn & Technol Shanghai Peoples R China Cognit & Intelligent Technol Lab Suzhou Peoples R China Minist Educ Engn Res Ctr & Robot Shanghai Peoples R China AI & Unmanned Syst Engn Res Ctr Jilin Prov Changchun Peoples R China

ISBN: (纸本)9798350353006

Fine-grained medical action analysis plays a vital role in improving medical skill training efficiency, but it faces the problems of data and algorithm shortage. Cardiopulmonary Resuscitation (CPR) is an essential skill in emergency treatment. Currently, the assessment of CPR skills mainly depends on dummies and trainers, leading to high training costs and low efficiency. For the first time, this paper constructs a vision-based system to complete error action recognition and skill assessment in CPR. Specifically, we define 13 types of single-error actions and 74 types of composite error actions during external cardiac compression and then develop a video dataset named CPR-Coach. By taking the CPR-Coach as a benchmark, this paper investigates and compares the performance of existing action recognition models based on different data modalities. To solve the unavoidable "Single-class Training & Multi-class Testing" problem, we propose a human-cognition-inspired framework named ImagineNet to improve the model's multi-error recognition performance under restricted supervision. Extensive comparison and actual deployment experiments verify the effectiveness of the framework. We hope this work could bring new inspiration to the computer vision and medical skills training communities simultaneously. The dataset and the code are publicly available on https://***/Shunli-Wang/CPR- Coach.

关键词： Composite Error Action recognition CPR Training Human Action recognition

来源：评论

学校读者我要写书评

暂无评论

DePT: Decoupled Prompt Tuning

DePT: Decoupled Prompt Tuning

引用

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

作者： Zhang, Ji Wu, Shihan Gao, Lianli Shen, Heng Tao Song, Jingkuan Univ Elect Sci & Technol China UESTC Chengdu Peoples R China UESTC Shenzhen Inst Adv Study Chengdu Peoples R China Tongji Univ Shanghai Peoples R China

ISBN: (纸本)9798350353006

This work breaks through the Base-New Tradeoff (BNT) dilemma in prompt tuning, i.e., the better the tuned model generalizes to the base (or target) task, the worse it generalizes to new tasks, and vice versa. Specifically, through an in-depth analysis of the learned features of the base and new tasks, we observe that the BNT stems from a channel bias issue - the vast majority of feature channels are occupied by base-specific knowledge, leading to the collapse of task-shared knowledge important to new tasks. To address this, we propose the Decoupled Prompt Tuning (DePT) framework, which decouples base-specific knowledge from feature channels into an isolated feature space during prompt tuning, so as to maximally preserve task-shared knowl-edge in the original feature space for achieving better zero-shot generalization on new tasks. Importantly, our DePT is orthogonal to existing prompt tuning approaches, and can enhance them with negligible additional computational cost. Extensive experiments on several datasets show the flexibility and effectiveness of DePT. Code is available at https://***/Koorye/DePT.

关键词： Feature decoupling Few-shot learning Prompt tuning vision and language

来源：评论

学校读者我要写书评

暂无评论

GeneAvatar: Generic Expression-Aware Volumetric Head Avatar Editing from a Single Image

GeneAvatar: Generic Expression-Aware Volumetric Head Avatar ...

引用

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

作者： Bao, Chong Zhang, Yinda Li, Yuan Zhang, Xiyu Yang, Bangbang Bao, Hujun Pollefeys, Marc Zhang, Guofeng Cui, Zhaopeng Zhejiang Univ State Key Lab CAD & CG Hangzhou Peoples R China Google Mountain View CA 94043 USA Swiss Fed Inst Technol Zurich Switzerland ByteDance Beijing Peoples R China

ISBN: (纸本)9798350353013;9798350353006

Recently, we have witnessed the explosive growth of various volumetric representations in modeling animatable head avatars. However, due to the diversity of frameworks, there is no practical method to support high-level applications like 3D head avatar editing across different representations. In this paper, we propose a generic avatar editing approach that can be universally applied to various 3DMM-driving volumetric head avatars. To achieve this goal, we design a novel expression-aware modification generative model, which enables lift 2D editing from a single image to a consistent 3D modification field. To ensure the effectiveness of the generative modification process, we develop several techniques, including an expression-dependent modification distillation scheme to draw knowledge from the large-scale head avatar model and 2D facial texture editing tools, implicit latent space guidance to enhance model convergence, and a segmentation-based loss reweight strategy for fine-grained texture inversion. Extensive experiments demonstrate that our method delivers high-quality and consistent results across multiple expression and viewpoints. Project page: https://***/geneavatar/.

关键词： 3D computer vision avatar editing head avatar neural rendering

来源：评论

学校读者我要写书评

暂无评论

Absolute Pose from One or Two Scaled and Oriented Features

Absolute Pose from One or Two Scaled and Oriented Features

引用

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

作者： Ventura, Jonathan Kukelova, Zuzana Sattler, Torsten Barath, Daniel Cal Poly Dept Comp Sci & Software Engn San Luis Obispo CA USA Czech Tech Univ Visual Recognit Grp Fac Elect Engn Prague Czech Republic Czech Tech Univ Czech Inst Informat Robot & Cybernet Prague Czech Republic Swiss Fed Inst Technol Dept Comp Sci Comp Vision & Geometry Grp Zurich Switzerland

ISBN: (纸本)9798350353006

Keypoints used for image matching often include an estimate of the feature scale and orientation. While recent work has demonstrated the advantages of using feature scales and orientations for relative pose estimation, relatively little work has considered their use for absolute pose estimation. We introduce minimal solutions for absolute pose from two oriented feature correspondences in the general case, or one scaled and oriented correspondence given a known vertical direction. Nowadays, assuming a known direction is not particularly restrictive as modern consumer devices, such as smartphones or drones, are equipped with Inertial Measurement Units (IMU) that provide the gravity direction by default. Compared to traditional absolute pose methods requiring three point correspondences, our solvers need a smaller minimal sample, reducing the cost and complexity of robust estimation. Evaluations on large-scale and public real datasets demonstrate the advantage of our methods for fast and accurate localization in challenging conditions. Code is available at https: //***/danini/absolute-pose-from-orientedand-scaled-features.

关键词： absolute pose computer vision geometric vision image-based localization minimal solver

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 << < 23 24 25 26 27 28 29 30 31 32 > >>

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：