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We present a novel methodology based on geometric approach to simulate magnification lens effects. Our aim is to promote new applications of powerful geometric modeling techniques in visual computing. Conventional image…

Graphics · Computer Science 2013-08-05 Bo Li , Xin Zhao

We introduce VERTEX, an effective solution to recover 3D shape and intrinsic texture of vehicles from uncalibrated monocular input in real-world street environments. To fully utilize the template prior of vehicles, we propose a novel…

Computer Vision and Pattern Recognition · Computer Science 2021-03-30 Xiaochen Zhao , Zerong Zheng , Chaonan Ji , Zhenyi Liu , Siyou Lin , Tao Yu , Jinli Suo , Yebin Liu

High-quality 3D assets are essential for various applications in computer graphics and 3D vision but remain scarce due to significant acquisition costs. To address this shortage, we introduce Elevate3D, a novel framework that transforms…

Graphics · Computer Science 2025-07-16 Nuri Ryu , Jiyun Won , Jooeun Son , Minsu Gong , Joo-Haeng Lee , Sunghyun Cho

Conventional production workflow of high-precision mesh assets necessitates a cumbersome and laborious process of manual sculpting by specialized 3D artists/modelers. The recent years have witnessed remarkable advances in AI-empowered 3D…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Qijian Zhang , Xiaozheng Jian , Xuan Zhang , Wenping Wang , Junhui Hou

We present TexMesh, a novel approach to reconstruct detailed human meshes with high-resolution full-body texture from RGB-D video. TexMesh enables high quality free-viewpoint rendering of humans. Given the RGB frames, the captured…

Computer Vision and Pattern Recognition · Computer Science 2020-09-22 Tiancheng Zhi , Christoph Lassner , Tony Tung , Carsten Stoll , Srinivasa G. Narasimhan , Minh Vo

In this work, we introduce Unique3D, a novel image-to-3D framework for efficiently generating high-quality 3D meshes from single-view images, featuring state-of-the-art generation fidelity and strong generalizability. Previous methods based…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Kailu Wu , Fangfu Liu , Zhihan Cai , Runjie Yan , Hanyang Wang , Yating Hu , Yueqi Duan , Kaisheng Ma

Tracking objects in 3D space and predicting their 6DoF pose is an essential task in computer vision. State-of-the-art approaches often rely on object texture to tackle this problem. However, while they achieve impressive results, many…

Computer Vision and Pattern Recognition · Computer Science 2022-03-11 Manuel Stoiber , Martin Sundermeyer , Rudolph Triebel

In this paper, we propose a novel approach to reconstruct 3D human body shapes based on a sparse set of RGBD frames using a single RGBD camera. We specifically focus on the realistic settings where human subjects move freely during the…

Computer Vision and Pattern Recognition · Computer Science 2020-06-16 Xinxin Zuo , Sen Wang , Jiangbin Zheng , Weiwei Yu , Minglun Gong , Ruigang Yang , Li Cheng

This paper addresses the problem of generating textures for 3D mesh assets. Existing approaches often rely on image diffusion models to generate multi-view image observations, which are then transformed onto the mesh surface to produce a…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Xuyang Wang , Ziang Cheng , Zhenyu Li , Jiayu Yang , Haorui Ji , Pan Ji , Mehrtash Harandi , Richard Hartley , Hongdong Li

In this paper, we propose an efficient method for robust 3D self-portraits using a single RGBD camera. Benefiting from the proposed PIFusion and lightweight bundle adjustment algorithm, our method can generate detailed 3D self-portraits in…

Computer Vision and Pattern Recognition · Computer Science 2020-04-07 Zhe Li , Tao Yu , Chuanyu Pan , Zerong Zheng , Yebin Liu

This paper presents an effective method for generating a spatiotemporal (time-varying) texture map for a dynamic object using a single RGB-D camera. The input of our framework is a 3D template model and an RGB-D image sequence. Since there…

Computer Vision and Pattern Recognition · Computer Science 2021-08-23 Hyomin Kim , Jungeon Kim , Hyeonseo Nam , Jaesik Park , Seungyong Lee

Incremental scene reconstruction is essential to the navigation in robotics. Most of the conventional methods typically make use of either TSDF (truncated signed distance functions) volume or neural networks to implicitly represent the…

Robotics · Computer Science 2024-04-30 Shaofan Liu , Junbo Chen , Jianke Zhu

We propose a novel technique to register sparse 3D scans in the absence of texture. While existing methods such as KinectFusion or Iterative Closest Points (ICP) heavily rely on dense point clouds, this task is particularly challenging…

Computer Vision and Pattern Recognition · Computer Science 2020-10-13 Siddhant Ranade , Xin Yu , Shantnu Kakkar , Pedro Miraldo , Srikumar Ramalingam

Texture and material blending is one of the leading methods for adding variety to rendered virtual worlds, creating composite materials, and generating procedural content. When done naively, it can introduce either visible seams or contrast…

Graphics · Computer Science 2025-02-20 Bartlomiej Wronski

In this paper, we address the problem of 3D object mesh reconstruction from RGB videos. Our approach combines the best of multi-view geometric and data-driven methods for 3D reconstruction by optimizing object meshes for multi-view…

Computer Vision and Pattern Recognition · Computer Science 2019-03-21 Chen-Hsuan Lin , Oliver Wang , Bryan C. Russell , Eli Shechtman , Vladimir G. Kim , Matthew Fisher , Simon Lucey

The comparison of current image data with existing 3D model data of a scene provides an efficient method to keep models up to date. In order to transfer information between 2D and 3D data, a preliminary co-registration is necessary. In this…

Computer Vision and Pattern Recognition · Computer Science 2019-09-24 Sylvia Schmitz , Martin Weinmann , Boitumelo Ruf

We present a novel approach to reconstruct RGB-D indoor scene with plane primitives. Our approach takes as input a RGB-D sequence and a dense coarse mesh reconstructed by some 3D reconstruction method on the sequence, and generate a…

Computer Vision and Pattern Recognition · Computer Science 2019-05-27 Chao Wang , Xiaohu Guo

Objective visual quality assessment of 3D models is a fundamental issue in computer graphics. Quality assessment metrics may allow a wide range of processes to be guided and evaluated, such as level of detail creation, compression,…

Computer Vision and Pattern Recognition · Computer Science 2021-02-09 Jinjiang Guo , Vincent Vidal , Irene Cheng , Anup Basu , Atilla Baskurt , Guillaume Lavoue

Recent advances have enabled 3d object reconstruction approaches using a single off-the-shelf RGB-D camera. Although these approaches are successful for a wide range of object classes, they rely on stable and distinctive geometric or…

Computer Vision and Pattern Recognition · Computer Science 2017-04-04 Dimitrios Tzionas , Juergen Gall

Recently single-view 3D generation via Gaussian splatting has emerged and developed quickly. They learn 3D Gaussians from 2D RGB images generated from pre-trained multi-view diffusion (MVD) models, and have shown a promising avenue for 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Yiyang Shen , Kun Zhou , He Wang , Yin Yang , Tianjia Shao
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