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AR assistance for efficient dynamic target search

Computational Visual Media 2023年第1期9卷 177-194页

作者： Zixiang Zhao Jian Wu Lili Wang State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijingChina

When searching for a dynamic target in an unknown real world scene,search efficiency is greatly reduced if users lack information about the spatial structure of the *** target search studies,especially in robotics,focus on determining either the shortest path when the target’s position is known,or a strategy to find the target as quickly as possible when the target’s position is ***,the target’s position is often known intermittently in the real world,e.g.,in the case of using surveillance *** goal is to help user find a dynamic target efficiently in the real world when the target’s position is intermittently *** order to achieve this purpose,we have designed an AR guidance assistance system to provide optimal current directional guidance to users,based on searching a prediction *** assume that a certain number of depth cameras are fixed in a real scene to obtain dynamic target’s *** system automatically analyzes all possible meetings between the user and the target,and generates optimal directional guidance to help the user catch up with the target.A user study was used to evaluate our method,and its results showed that compared to free search and a top-view method,our method significantly improves target search efficiency.

关键词： augmented reality(AR) search guidance

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Structure guided texture inpainting through multi-scale patches and global optimization for image completion

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Science China(Information Sciences) 2014年第1期57卷 25-40页

作者： CHEN XiaoWu ZHOU Bin GUO Yu XU Fang ZHAO QinPing State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University

Automatic image completion can provide convenient editing of consumer *** image completion methods find the best patch locally and then copy it to the hole region for texture *** the best patch is fixed in size,it is hard to adapt these methods efciently either to various patterns or to content ***,salient image structures can be estimated and propagated to guide the texture inpainting process for more plausible *** paper presents a novel image completion method using structure guided texture *** do not require any interactions to achieve automatic two-stage image *** the structure completion stage,the salient structures around the hole region are detected,and then the missing structure curves are completed with Euler *** textures along the structure curves are completed through belief *** the texture inpainting stage,we propose multi-scale patches and global optimization to inpaint the remaining texture in the hole regions guided by the completed ***,with defined patch sizes,the hole region is divided into lattice patches,making it possible for multiple patch sizes to render multiscale descriptions of this image.A multi-scale graph is then built for the hole region and formulated as a posterior probability ***,using a simulated annealing based Markov chain Monte Carlo method,an inference algorithm is designed to find a global optimization solution for the posterior probability *** experiments show that our method can automatically complete the hole region and preserve plausible structure shapes of existing ones in various *** texture inpainting results are more convincing with guidance from the completed structures,and our method can guarantee and accelerate convergence of the global optimization.

关键词： image completion texture inpainting structure propagation global optimization

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ShadowGAN: Shadow synthesis for virtual objects with conditional adversarial networks

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Computational Visual Media 2019年第1期5卷 105-115页

作者： Shuyang Zhang Runze Liang Miao Wang University of Michigan Department of Computer Science and Technology Tsinghua University State Key Laboratory of Virtual Reality Technology and Systems Beihang University

We introduce ShadowGAN, a generative adversarial network(GAN) for synthesizing shadows for virtual objects inserted in images. Given a target image containing several existing objects with shadows,and an input source object with a specified insertion position, the network generates a realistic shadow for the source object. The shadow is synthesized by a generator; using the proposed local adversarial and global adversarial discriminators, the synthetic shadow's appearance is locally realistic in shape, and globally consistent with other objects' shadows in terms of shadow direction and area. To overcome the lack of training data,we produced training samples based on public 3D models and rendering technology. Experimental results from a user study show that the synthetic shadowed results look natural and authentic.

关键词： shadow synthesis deep learning generative adversarial networks image synthesis

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Learning Semantic Concepts from Noisy Media Collection for Automatic Image Annotation

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Chinese Journal of Electronics 2015年第4期24卷 790-794页

作者： TIAN Feng SHEN Xukun School of Computer and Information Technology Northeast Petroleum University State Key Laboratory of Virtual Reality Technology and Systems Beihang University

Along with the explosive growth of images, automatic image annotation has attracted great interest of various research communities. However, despite the great progress achieved in the past two decades, automatic annotation is still an important open problem in computer vision, and can hardly achieve satisfactory performance in real-world environment. In this paper, we address the problem of annotation when noise is interfering with the dataset. A semantic neighborhood learning model on noisy media collection is proposed. Missing labels are replenished, and semantic balanced neighborhood is construct. The model allows the integration of multiple label metric learning and local nonnegative sparse *** construct semantic consistent neighborhood for each sample, thus corresponding neighbors have higher global similarity, partial correlation, conceptual similarity along with semantic balance. Meanwhile, an iterative denoising method is also proposed. The method proposed makes a marked improvement as compared to the current state-ofthe-art.

关键词： Image annotation Noisy media collection Semantic neighborhood

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NURBS curve blending using extension

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2009年第4期10卷 570-576页

作者： Yong-jin LIU Rong-qi QIU Xiao-hui LIANG Tsinghua National Lab for Information Science and Technology Tsinghua University Beijing 100084 China State Key Lab of Virtual Reality Technology and Systems Beihang University Beijing 100191 China

Curve and surface blending is an important operation in CAD systems, in which a non-uniform rational B-spline （NURBS） has been used as the de facto standard. In local comer blending, two curves intersecting at that comer are first made disjoint, and then the third blending curve is added-in to smoothly join the two curves with G^1- or G^2-continuity. In this paper we present a study to solve the joint problem based on curve extension. The following nice properties of this extension algorithm are exploited in depth：（1） The parameterization of the original shapes does not change; （2） No additional fragments are created. Various examples are presented to demonstrate that our solution is simple and efficient.

关键词： Curve blending Curve fairing Curve extension Non-uniform rational B-spline （NURBS）

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Joint self-supervised and reference-guided learning for depth inpainting

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Computational Visual Media 2022年第4期8卷 597-612页

作者： Heng Wu Kui Fu Yifan Zhao Haokun Song Jia Li State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100191China

Depth information can benefit various computer vision tasks on both images and ***,depth maps may suffer from invalid values in many pixels,and also large *** improve such data,we propose a joint self-supervised and reference-guided learning approach for depth *** the self-supervised learning strategy,we introduce an improved spatial convolutional sparse coding module in which total variation regularization is employed to enhance the structural information while preserving edge *** module alternately learns a convolutional dictionary and sparse coding from a corrupted depth ***,both the learned convolutional dictionary and sparse coding are convolved to yield an initial depth map,which is effectively smoothed using local contextual *** reference-guided learning part is inspired by the fact that adjacent pixels with close colors in the RGB image tend to have similar depth *** thus construct a hierarchical joint bilateral filter module using the corresponding color image to fill in large *** summary,our approach integrates a convolutional sparse coding module to preserve local contextual information and a hierarchical joint bilateral filter module for filling using specific adjacent *** results show that the proposed approach works well for both invalid value restoration and large hole inpainting.

关键词： depth inpainting self-supervised learning reference-guided learning

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Modeling Garment Seam from a Single Image

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Journal of Computer Science & technology 2018年第3期33卷 463-474页

作者： Chen-Xu Zhang Xiao-Wu Chen Hong-Yu Wu Bin Zhou State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing 100191 China

We propose an automatic garment seam modeling framework to create a garment model with the seam structure from a single image. In order to achieve this, a marked seam image database and parametric seam models have been set up. Given a real seam image, we first identify the type of the seam image based on our marked semn image database and the seam parameters are parsed automatically by our sewing thread estimation method. Second the seam initial model is generated through the pre-defined parametric seam models. A garment model with the seam structure is finally obtained based on the seam position infrmation which users have marked on the garment. Moreover. we verify the effectiveness of our method with numerous experiments.

关键词： image-based 3D modeling garment modeling garment seam

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Monocular Video Guided Garment Simulation

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Journal of Computer Science & technology 2015年第3期30卷 528-539页

作者：李发明陈小武周彬卢飞翔郭侃符强 State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing 100191 China

We present a prototype to generate a garment-shape sequence guided by a monocular video sequence. It is a combination of a physically-based simulation and a boundary-based modification. Given a garment in the video worn on a mannequin, the simulation generates a garment initial shape by exploiting the mannequin shapes estimated from the video. The modification then deforms the simulated 3D shape into such a shape that matches the garment 2D boundary extracted from the video. According to the matching correspondences between the vertices on the shape and the points on the boundary, the modification is implemented by attracting the matched vertices and their neighboring vertices. For best-matching correspondences and efficient performance, three criteria are introduced to select the candidate vertices for matching. Since modifying each garment shape independently may cause inter-frame oscillations, changes by the modification are also propagated from one frame to the next frame. As a result, the generated garment 3D shape sequence is stable and similar to the garment video sequence. We demonstrate the effectiveness of our prototype with a number of examples.

关键词： garment simulation monocular video shape correspondence

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Dynamic Characteristic Analysis and Experiment for Integral Impeller Based on Cyclic Symmetry Analysis Method

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Chinese Journal of Aeronautics 2012年第5期25卷 804-810页

作者： WU Qiong ZHANG Yidu ZHANG Hongwei State Key Laboratory of Virtual Reality Technology and Systems School of Mechanical Engineering and AutomationBeihang UniversityBeijing 100191China

A cyclic symmetry analysis method is proposed for analyzing the dynamic characteristic problems of thin walled integral im- peller. Reliability and feasibility of the present method are investigated by means of simulation and experiment. The fundamental cyclic symmetry equations and the solutions of these equations are derived for the cyclic symmetry structure. The computational efficiency analysis between whole and part is performed. Comparison of results obtained by the finite element analysis （FEA） and experiment shows that the local dynamic characteristic of integral impeller has consistency with the single cyclic symmetry blade. When the integral impeller is constrained and the thin walled blade becomes a concerned object in analysis, the dynamic characteristic of integral impeller can be replaced by the cyclic symmetry blade approximately. Hence, a cyclic symmetry analy- sis method is effectively used to improve efficiency and obtain more information of parameters for dynamic characteristic of integral impellers.

关键词： dynamic characteristic cyclic symmetry impellers simulation finite element analysis blade

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Text2Earth: Unlocking Text-driven Remote Sensing Image Generation with a Global-Scale Dataset and a Foundation Model

arXiv

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arXiv 2025年

作者： Liu, Chenyang Chen, keyan Zhao, Rui Zou, Zhengxia Shi, Zhenwei The Department of Aerospace Intelligent Science and Technology School of Astronautics The State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing100191 China The Key Laboratory of Spacecraft Design Optimization and Dynamic Simulation Technologies Ministry of Education China Shanghai Artificial Intelligence Laboratory Shanghai200232 China Shen Yuan Honors College of Beihang University Beijing100191 China The Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore

Recently, generative foundation models have significantly advanced large-scale text-driven natural image generation and have become a prominent research trend across various vertical domains. However, in the remote sensing field, there is still a lack of research on large-scale text-to-image (text2image) generation technology. Existing remote sensing image-text datasets are small in scale and confined to specific geographic areas and scene types. Besides, existing text2image methods have struggled to achieve global-scale, multi-resolution controllable, and unbounded image generation. To address these challenges, this paper presents two key contributions: the Git-10M dataset and the Text2Earth foundation model. Git-10M is a global-scale image-text dataset comprising 10.5 million image-text pairs, 5 times larger than the previous largest one. The dataset contains essential resolution information and covers a wide range of geographic scenes and contains essential geospatial metadata, significantly surpassing existing datasets in both size and diversity. Building on Git-10M, we propose Text2Earth, a 1.3 billion parameter generative foundation model based on the diffusion framework to model global-scale remote sensing scenes. Text2Earth integrates a resolution guidance mechanism, enabling users to specify image resolutions. A dynamic condition adaptation strategy is proposed for training and inference to improve image generation quality. Text2Earth not only excels in zero-shot text2image generation but also demonstrates robust generalization and flexibility across multiple tasks, including unbounded scene construction, image editing, and cross-modal image generation. This robust capability surpasses previous models restricted to the basic fixed size and limited scene types. On the previous text2image benchmark dataset, Text2Earth outperfoms previous models with a significant improvement of +26.23 FID and +20.95% Zero-shot Cls-OA metric. Our project page is https://chen-y

关键词： Optical remote sensing

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