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

249 篇 会议

馆藏范围

249 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

249 篇 工学
- 249 篇 计算机科学与技术...
- 83 篇 软件工程

主题

249 篇 3d from multi-vi...
1 篇 dynamic scenes
1 篇 differentiable r...
1 篇 gaussian splatti...
1 篇 depth refinement
1 篇 occupancy foreca...
1 篇 volume rendering
1 篇 neural rendering
1 篇 novel view synth...
1 篇 occupancy predic...
1 篇 human performanc...
1 篇 compact gaussian...
1 篇 mesh
1 篇 surface reconstr...
1 篇 depth completion

机构

13 篇 zhejiang univ pe...
12 篇 chinese univ hon...
10 篇 tech univ munich...
9 篇 univ hong kong p...
8 篇 shanghai ai lab ...
7 篇 univ sci & techn...
7 篇 shanghai jiao to...
7 篇 simon fraser uni...
7 篇 zhejiang univ st...
6 篇 univ toronto on
6 篇 smartmore people...
6 篇 tsinghua univ pe...
5 篇 carnegie mellon ...
5 篇 huawei noahs ark...
5 篇 lund univ lund
4 篇 peking univ peop...
4 篇 tsinghua univ sc...
4 篇 tsinghua univ de...
4 篇 wayne state univ...
4 篇 australian natl ...

作者

7 篇 zhou xiaowei
6 篇 niessner matthia...
6 篇 jia jiaya
6 篇 peng sida
6 篇 bao hujun
5 篇 tagliasacchi and...
5 篇 guibas leonidas
5 篇 liu yu-shen
4 篇 han xiaoguang
4 篇 yao ting
4 篇 qi xiaojuan
4 篇 dai angela
4 篇 theobalt christi...
4 篇 han zhizhong
4 篇 larsson viktor
3 篇 liu yuan
3 篇 lu cewu
3 篇 pollefeys marc
3 篇 chen yukang
3 篇 kim changil

语言

249 篇 英文

检索条件"主题词=3D from multi-view and sensors"

共 249 条记录，以下是171-180 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：

REC-MV: REconstructing 3d dynamic Cloth from Monocular Videos

REC-MV: REconstructing 3D Dynamic Cloth from Monocular Video...

引用

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Qiu, Lingteng Chen, Guanying Zhou, Jiapeng Xu, Mutian Wang, Junle Han, Xiaoguang CUHKSZ SSE Shenzhen Peoples R China CUHKSZ FNii Shenzhen Peoples R China Tencent Shenzhen Peoples R China

ISBN: (纸本)9798350301298

Reconstructing dynamic 3d garment surfaces with open boundaries from monocular videos is an important problem as it provides a practical and low-cost solution for clothes digitization. Recent neural rendering methods achieve high-quality dynamic clothed human reconstruction results from monocular video, but these methods cannot separate the garment surface from the body. Moreover, despite existing garment reconstruction methods based on feature curve representation demonstrating impressive results for garment reconstruction from a single image, they struggle to generate temporally consistent surfaces for the video input. To address the above limitations, in this paper, we formulate this task as an optimization problem of 3d garment feature curves and surface reconstruction from monocular video. We introduce a novel approach, called REC-MV, to jointly optimize the explicit feature curves and the implicit signed distance field (SdF) of the garments. Then the open garment meshes can be extracted via garment template registration in the canonical space. Experiments on multiple casually captured datasets show that our approach outperforms existing methods and can produce high-quality dynamic garment surfaces. The source code is available at https://***/GAP-LAB-CUHK-SZ/REC-MV.

关键词： 3d from multi-view and sensors

来源：评论

学校读者我要写书评

暂无评论

Compressing Volumetric Radiance Fields to 1 MB

Compressing Volumetric Radiance Fields to 1 MB

引用

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Li, Lingzhi Shen, Zhen Wang, Zhongshu Shen, Li Bo, Liefeng Alibaba Grp Beijing Peoples R China

ISBN: (纸本)9798350301298

Approximating radiance fields with discretized volumetric grids is one of promising directions for improving NeRFs, represented by methods like dVGO, Plenoxels and TensoRF, which achieve super-fast training convergence and real-time rendering. However, these methods typically require a tremendous storage overhead, costing up to hundreds of megabytes of disk space and runtime memory for a single scene. We address this issue in this paper by introducing a simple yet effective framework, called vector quantized radiance fields (VQRF), for compressing these volume-grid-based radiance fields. We first present a robust and adaptive metric for estimating redundancy in grid models and performing voxel pruning by better exploring intermediate outputs of volumetric rendering. A trainable vector quantization is further proposed to improve the compactness of grid models. In combination with an efficient joint tuning strategy and post-processing, our method can achieve a compression ratio of 100x by reducing the overall model size to 1 MB with negligible loss on visual quality. Extensive experiments demonstrate that the proposed framework is capable of achieving unrivaled performance and well generalization across multiple methods with distinct volumetric structures, facilitating the wide use of volumetric radiance fields methods in real-world applications. Code is available at https://***/AlgoHunt/VQRF.

关键词： 3d from multi-view and sensors

来源：评论

学校读者我要写书评

暂无评论

Neural Lens Modeling

Neural Lens Modeling

引用

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Xian, Wenqi Bozic, Aljaz Snavely, Noah Lassner, Christoph Meta Real Labs Res Menlo Pk CA 94025 USA Cornell Univ Ithaca NY 14853 USA

ISBN: (纸本)9798350301298

Recent methods for 3d reconstruction and rendering increasingly benefit from end-to-end optimization of the entire image formation process. However, this approach is currently limited: effects of the optical hardware stack and in particular lenses are hard to model in a unified way. This limits the quality that can be achieved for camera calibration and the fidelity of the results of 3d reconstruction. In this paper, we propose NeuroLens, a neural lens model for distortion and vignetting that can be used for point projection and ray casting and can be optimized through both operations. This means that it can (optionally) be used to perform pre-capture calibration using classical calibration targets, and can later be used to perform calibration or refinement during 3d reconstruction, e.g., while optimizing a radiance field. To evaluate the performance of our proposed model, we create a comprehensive dataset assembled from the Lensfun database with a multitude of lenses. Using this and other real-world datasets, we show that the quality of our proposed lens model outperforms standard packages as well as recent approaches while being much easier to use and extend. The model generalizes across many lens types and is trivial to integrate into existing 3d reconstruction and rendering systems. Visit our project website at: https://***.

关键词： 3d from multi-view and sensors

来源：评论

学校读者我要写书评

暂无评论

NeuralEditor: Editing Neural Radiance Fields via Manipulating Point Clouds

NeuralEditor: Editing Neural Radiance Fields via Manipulatin...

引用

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Chen, Jun-Kun Lyu, Jipeng Wang, Yu-Xiong Univ Illinois Champaign IL 61820 USA Peking Univ Beijing Peoples R China

ISBN: (纸本)9798350301298

This paper proposes NeuralEditor that enables neural radiance fields (NeRFs) natively editable for general shape editing tasks. despite their impressive results on novel-view synthesis, it remains a fundamental challenge for NeRFs to edit the shape of the scene. Our key insight is to exploit the explicit point cloud representation as the underlying structure to construct NeRFs, inspired by the intuitive interpretation of NeRF rendering as a process that projects or "plots" the associated 3d point cloud to a 2d image plane. To this end, NeuralEditor introduces a novel rendering scheme based on deterministic integration within K-d tree-guided density-adaptive voxels, which produces both high-quality rendering results and precise point clouds through optimization. NeuralEditor then performs shape editing via mapping associated points between point clouds. Extensive evaluation shows that NeuralEditor achieves state-of-the-art performance in both shape deformation and scene morphing tasks. Notably, NeuralEditor supports both zero-shot inference and further fine-tuning over the edited scene. Our code, benchmark, and demo video are available at ***/NeuralEditor.

关键词： 3d from multi-view and sensors

来源：评论

学校读者我要写书评

暂无评论

NeFII: Inverse Rendering for Reflectance decomposition with Near-Field Indirect Illumination

NeFII: Inverse Rendering for Reflectance Decomposition with ...

引用

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Wu, Haoqian Hu, Zhipeng Li, Lincheng Zhang, Yonggiang Fan, Changjie Yu, Xin NetEase Fuxi AI Lab Beijing Peoples R China Zhejiang Univ Hangzhou Peoples R China Univ Queensland Brisbane Qld Australia

ISBN: (纸本)9798350301298

Inverse rendering methods aim to estimate geometry, materials and illumination from multi-view RGB images. In order to achieve better decomposition, recent approaches attempt to model indirect illuminations reflected from different materials via Spherical Gaussians (SG), which, however, tends to blur the high-frequency reflection details. In this paper, we propose an end-to-end inverse rendering pipeline that decomposes materials and illumination from multi-view images, while considering near-field indirect illumination. In a nutshell, we introduce the Monte Carlo sampling based path tracing and cache the indirect illumination as neural radiance, enabling a physics-faithful and easy-to-optimize inverse rendering method. To enhance efficiency and practicality, we leverage SG to represent the smooth environment illuminations and apply importance sampling techniques. To supervise indirect illuminations from unobserved directions, we develop a novel radiance consistency constraint between implicit neural radiance and path tracing results of unobserved rays along with the joint optimization of materials and illuminations, thus significantly improving the decomposition performance. Extensive experiments demonstrate that our method outperforms the state-of-the-art on multiple synthetic and real datasets, especially in terms of inter-reflection decomposition.

关键词： 3d from multi-view and sensors

来源：评论

学校读者我要写书评

暂无评论

SegLoc: Learning Segmentation-based Representations for Privacy-Preserving Visual Localization

SegLoc: Learning Segmentation-based Representations for Priv...

引用

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Pietrantoni, Maxime Humenberger, Martin Sattler, Torsten Csurka, Gabriela Czech Tech Univ Fac Elect Engn Prague Czech Republic Czech Tech Univ Czech Inst Informat Robot & Cybernet Prague Czech Republic NAVER LABS Europe Meylan France

ISBN: (纸本)9798350301298

Inspired by properties of semantic segmentation, in this paper we investigate how to leverage robust image segmentation in the context of privacy-preserving visual localization. We propose a new localization framework, SegLoc, that leverages image segmentation to create robust, compact, and privacy-preserving scene representations, i.e., 3d maps. We build upon the correspondence-supervised, fine-grained segmentation approach from [42], making it more robust by learning a set of cluster labels with discriminative clustering, additional consistency regularization terms and we jointly learn a global image representation along with a dense local representation. In our localization pipeline, the former will be used for retrieving the most similar images, the latter to refine the retrieved poses by minimizing the label inconsistency between the 3d points of the map and their projection onto the query image. In various experiments, we show that our proposed representation allows to achieve (close-to) state-of-the-art pose estimation results while only using a compact 3d map that does not contain enough information about the original images for an attacker to reconstruct personal information.

关键词： 3d from multi-view and sensors

来源：评论

学校读者我要写书评

暂无评论

Octree Guided Unoriented Surface Reconstruction

Octree Guided Unoriented Surface Reconstruction

引用

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Koneputugodage, Chamin Hewa Ben-Shabat, Yizhak Gould, Stephen Australian Natl Univ Canberra ACT Australia Tech Israel Inst Technol Haifa Israel

ISBN: (纸本)9798350301298

We address the problem of surface reconstruction from unoriented point clouds. Implicit neural representations (INRs) have become popular for this task, but when information relating to the inside versus outside of a shape is not available (such as shape occupancy, signed distances or surface normal orientation) optimization relies on heuristics and regularizers to recover the surface. These methods can be slow to converge and easily get stuck in local minima. We propose a two-step approach, OG-INR, where we (1) construct a discrete octree and label what is inside and outside (2) optimize for a continuous and high-fidelity shape using an INR that is initially guided by the octree's labelling. To solve for our labelling, we propose an energy function over the discrete structure and provide an efficient move-making algorithm that explores many possible labellings. Furthermore we show that we can easily inject knowledge into the discrete octree, providing a simple way to influence the result from the continuous INR. We evaluate the effectiveness of our approach on two unoriented surface reconstruction datasets and show competitive performance compared to other unoriented, and some oriented, methods. Our results show that the exploration by the move-making algorithm avoids many of the bad local minima reached by purely gradient descent optimized methods (see Figure 1).

关键词： 3d from multi-view and sensors

来源：评论

学校读者我要写书评

暂无评论

SteerNeRF: Accelerating NeRF Rendering via Smooth viewpoint Trajectory

SteerNeRF: Accelerating NeRF Rendering via Smooth Viewpoint ...

引用

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Li, Sicheng Li, Hao Wang, Yue Liao, Yiyi Yu, Lu Zhejiang Univ Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9798350301298

Neural Radiance Fields (NeRF) have demonstrated superior novel view synthesis performance but are slow at rendering. To speed up the volume rendering process, many acceleration methods have been proposed at the cost of large memory consumption. To push the frontier of the efficiency-memory trade-off, we explore a new perspective to accelerate NeRF rendering, leveraging a key fact that the viewpoint change is usually smooth and continuous in interactive viewpoint control. This allows us to leverage the information of preceding viewpoints to reduce the number of rendered pixels as well as the number of sampled points along the ray of the remaining pixels. In our pipeline, a low-resolution feature map is rendered first by volume rendering, then a lightweight 2d neural renderer is applied to generate the output image at target resolution leveraging the features of preceding and current frames. We show that the proposed method can achieve competitive rendering quality while reducing the rendering time with little memory overhead, enabling 30FPS at 1080P image resolution with a low memory footprint.

关键词： 3d from multi-view and sensors

来源：评论

学校读者我要写书评

暂无评论

Learning Visibility Field for detailed 3d Human Reconstruction and Relighting

Learning Visibility Field for Detailed 3D Human Reconstructi...

引用

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Zheng, Ruichen Li, Peng Wang, Haoqian Yu, Tao Tsinghua Univ Beijing Peoples R China Weilan Tech Beijing Peoples R China

ISBN: (纸本)9798350301298

detailed 3d reconstruction and photo-realistic relighting of digital humans are essential for various applications. To this end, we propose a novel sparse-view 3d human reconstruction framework that closely incorporates the occupancy field and albedo field with an additional visibility field-it not only resolves occlusion ambiguity in multiview feature aggregation, but can also be used to evaluate light attenuation for self-shadowed relighting. To enhance its training viability and efficiency, we discretize visibility onto a fixed set of sample directions and supply it with coupled geometric 3d depth feature and local 2d image feature. We further propose a novel rendering-inspired loss, namely TransferLoss, to implicitly enforce the alignment between visibility and occupancy field, enabling end-to-end joint training. Results and extensive experiments demonstrate the effectiveness of the proposed method, as it surpasses state-of-the-art in terms of reconstruction accuracy while achieving comparably accurate relighting to ray-traced ground truth.

关键词： 3d from multi-view and sensors

来源：评论

学校读者我要写书评

暂无评论

Gated Stereo: Joint depth Estimation from Gated and Wide-Baseline Active Stereo Cues

Gated Stereo: Joint Depth Estimation from Gated and Wide-Bas...

引用

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Walz, Stefanie Bijelic, Mario Ramazzina, Andrea Walia, Amanpreet Mannan, Fahim Heide, Felix Mercedes Benz Stuttgart Germany Princeton Univ Princeton NJ 08544 USA Algolux Montreal PQ Canada

ISBN: (纸本)9798350301298

We propose Gated Stereo, a high-resolution and long-range depth estimation technique that operates on active gated stereo images. Using active and high dynamic range passive captures, Gated Stereo exploits multi-view cues alongside time-of-flight intensity cues from active gating. To this end, we propose a depth estimation method with a monocular and stereo depth prediction branch which are combined in a final fusion stage. Each block is supervised through a combination of supervised and gated self-supervision losses. To facilitate training and validation, we acquire a long-range synchronized gated stereo dataset for automotive scenarios. We find that the method achieves an improvement of more than 50% MAE compared to the next best RGB stereo method, and 74% MAE to existing monocular gated methods for distances up to 160 m. Our code, models and datasets are available here(1).

关键词： 3d from multi-view and sensors

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25页 << < 14 15 16 17 18 19 20 21 22 23 > >>

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：