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We propose a novel deep reinforcement learning-based approach for 3D object reconstruction from monocular images. Prior works that use mesh representations are template based. Thus, they are limited to the reconstruction of objects that…

Computer Vision and Pattern Recognition · Computer Science 2021-09-27 Tarek Ben Charrada , Hedi Tabia , Aladine Chetouani , Hamid Laga

Reconstructing object geometry and material from multiple views typically requires optimization. Differentiable path tracing is an appealing framework as it can reproduce complex appearance effects. However, it is difficult to use due to…

Computer Vision and Pattern Recognition · Computer Science 2020-12-09 Purvi Goel , Loudon Cohen , James Guesman , Vikas Thamizharasan , James Tompkin , Daniel Ritchie

This paper addresses the limitations of neural rendering-based multi-view surface reconstruction methods, which require an additional mesh extraction step that is inconvenient and would produce poor-quality surfaces with mesh aliasing,…

Computer Vision and Pattern Recognition · Computer Science 2025-08-26 Qitong Zhang , Jieqing Feng

Recovering a textured 3D mesh from a monocular image is highly challenging, particularly for in-the-wild objects that lack 3D ground truths. In this work, we present MeshInversion, a novel framework to improve the reconstruction by…

Computer Vision and Pattern Recognition · Computer Science 2022-07-21 Junzhe Zhang , Daxuan Ren , Zhongang Cai , Chai Kiat Yeo , Bo Dai , Chen Change Loy

We introduce PixARMesh, a method to autoregressively reconstruct complete 3D indoor scene meshes directly from a single RGB image. Unlike prior methods that rely on implicit signed distance fields and post-hoc layout optimization, PixARMesh…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Xiang Zhang , Sohyun Yoo , Hongrui Wu , Chuan Li , Jianwen Xie , Zhuowen Tu

Recent advancements in 3D robotic manipulation have improved grasping of everyday objects, but transparent and specular materials remain challenging due to depth sensing limitations. While several 3D reconstruction and depth completion…

Robotics · Computer Science 2025-06-23 Mingxu Zhang , Xiaoqi Li , Jiahui Xu , Kaichen Zhou , Hojin Bae , Yan Shen , Chuyan Xiong , Hao Dong

Open-world 3D reconstruction models have recently garnered significant attention. However, without sufficient 3D inductive bias, existing methods typically entail expensive training costs and struggle to extract high-quality 3D meshes. In…

Computer Vision and Pattern Recognition · Computer Science 2024-08-20 Minghua Liu , Chong Zeng , Xinyue Wei , Ruoxi Shi , Linghao Chen , Chao Xu , Mengqi Zhang , Zhaoning Wang , Xiaoshuai Zhang , Isabella Liu , Hongzhi Wu , Hao Su

We present a unified framework tackling two problems: class-specific 3D reconstruction from a single image, and generation of new 3D shape samples. These tasks have received considerable attention recently; however, existing approaches rely…

Computer Vision and Pattern Recognition · Computer Science 2018-11-16 Paul Henderson , Vittorio Ferrari

Capturing the 3D geometry of transparent objects is a challenging task, ill-suited for general-purpose scanning and reconstruction techniques, since these cannot handle specular light transport phenomena. Existing state-of-the-art methods,…

Graphics · Computer Science 2020-09-22 Jiahui Lyu , Bojian Wu , Dani Lischinski , Daniel Cohen-Or , Hui Huang

We present a new effective way for performance capture of deforming meshes with fine-scale time-varying surface detail from multi-view video. Our method builds up on coarse 4D surface reconstructions, as obtained with commonly used…

Computer Vision and Pattern Recognition · Computer Science 2016-02-08 Nadia Robertini , Edilson De Aguiar , Thomas Helten , Christian Theobalt

Mesh repair is a long-standing challenge in computer graphics and related fields. Converting defective meshes into watertight manifold meshes can greatly benefit downstream applications such as geometric processing, simulation, fabrication,…

Graphics · Computer Science 2023-09-04 Zhongtian Zheng , Xifeng Gao , Zherong Pan , Wei Li , Peng-Shuai Wang , Guoping Wang , Kui Wu

Reconstructing the three-dimensional (3D) geometry of object surfaces is essential for robot perception, yet vision-based approaches are generally unreliable under low illumination or occlusion. This limitation motivates the design of a…

Robotics · Computer Science 2026-01-21 Guanyu Xu , Jiaqi Wang , Dezhong Tong , Xiaonan Huang

The 3D Morphable Model (3DMM), which is a Principal Component Analysis (PCA) based statistical model that represents a 3D face using linear basis functions, has shown promising results for reconstructing 3D faces from single-view…

Computer Vision and Pattern Recognition · Computer Science 2021-08-17 Harim Jung , Myeong-Seok Oh , Seong-Whan Lee

Shape-from-Template (SfT) methods estimate 3D surface deformations from a single monocular RGB camera while assuming a 3D state known in advance (a template). This is an important yet challenging problem due to the under-constrained nature…

Computer Vision and Pattern Recognition · Computer Science 2022-03-23 Navami Kairanda , Edith Tretschk , Mohamed Elgharib , Christian Theobalt , Vladislav Golyanik

The world around us is full of soft objects we perceive and deform with dexterous hand movements. For a robotic hand to control soft objects, it has to acquire online state feedback of the deforming object. While RGB-D cameras can collect…

Computer Vision and Pattern Recognition · Computer Science 2024-03-28 Elham Amin Mansour , Hehui Zheng , Robert K. Katzschmann

Reconstructing high-fidelity 3D facial texture from a single image is a quite challenging task due to the lack of complete face information and the domain gap between the 3D face and 2D image. Further, obtaining re-renderable 3D faces has…

Computer Vision and Pattern Recognition · Computer Science 2022-06-07 Mingxin Yang , Jianwei Guo , Zhanglin Cheng , Xiaopeng Zhang , Dong-Ming Yan

We propose an analysis-by-synthesis method for fast multi-view 3D reconstruction of opaque objects with arbitrary materials and illumination. State-of-the-art methods use both neural surface representations and neural rendering. While…

Computer Vision and Pattern Recognition · Computer Science 2022-12-09 Markus Worchel , Rodrigo Diaz , Weiwen Hu , Oliver Schreer , Ingo Feldmann , Peter Eisert

Visual reconstruction of fast non-rigid object deformations over time is a challenge for conventional frame-based cameras. In this paper, we propose a novel approach for reconstructing such deformations using measurements from event-based…

Computer Vision and Pattern Recognition · Computer Science 2022-11-15 Yuxuan Xue , Haolong Li , Stefan Leutenegger , Jörg Stückler

We address the problem of recovering the 3D geometry of a human face from a set of facial images in multiple views. While recent studies have shown impressive progress in 3D Morphable Model (3DMM) based facial reconstruction, the settings…

Computer Vision and Pattern Recognition · Computer Science 2019-04-10 Fanzi Wu , Linchao Bao , Yajing Chen , Yonggen Ling , Yibing Song , Songnan Li , King Ngi Ngan , Wei Liu

Texture reconstruction techniques generally suffer from the errors in keyframe poses. We present a non-iterative method for seamless texture reconstruction of a given 3D scene. Our method finds the best texture alignment in a single shot…

Computer Vision and Pattern Recognition · Computer Science 2020-11-03 Mohammad Rouhani , Matthieu Fradet , Caroline Baillard