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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

Semantic 3D building models are widely available and used in numerous applications. Such 3D building models display rich semantics but no fa\c{c}ade openings, chiefly owing to their aerial acquisition techniques. Hence, refining models'…

Computer Vision and Pattern Recognition · Computer Science 2023-03-13 Olaf Wysocki , Eleonora Grilli , Ludwig Hoegner , Uwe Stilla

Non-parametric mesh reconstruction has recently shown significant progress in 3D hand and body applications. In these methods, mesh vertices and edges are visible to neural networks, enabling the possibility to establish a direct mapping…

Computer Vision and Pattern Recognition · Computer Science 2022-10-18 Shijian Jiang , Guwen Han , Danhang Tang , Yang Zhou , Xiang Li , Jiming Chen , Qi Ye

Aerial robots play a vital role in various applications where the situational awareness of the robots concerning the environment is a fundamental demand. As one such use case, drones in GPS-denied environments require equipping with…

Robotics · Computer Science 2024-06-24 Ahmed Radwan , Ali Tourani , Hriday Bavle , Holger Voos , Jose Luis Sanchez-Lopez

Reconstructing surfaces from normals is a key component of photometric stereo. This work introduces an adaptive surface triangulation in the image domain and afterwards performs the normal integration on a triangle mesh. Our key insight is…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Moritz Heep , Eduard Zell

We present a deep learning approach to reconstruct scene appearance from unstructured images captured under collocated point lighting. At the heart of Deep Reflectance Volumes is a novel volumetric scene representation consisting of…

Computer Vision and Pattern Recognition · Computer Science 2020-07-21 Sai Bi , Zexiang Xu , Kalyan Sunkavalli , Miloš Hašan , Yannick Hold-Geoffroy , David Kriegman , Ravi Ramamoorthi

Open-vocabulary 3D affordance detection requires localizing interaction regions on point clouds given novel affordance descriptions. Recent methods extend multimodal large language models (MLLMs) with special output tokens that are decoded…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Haowen Sun , Shaolong Zhang , Mingyang Li , Chengzhong Ma , Xinzhe Chen , Qiongjie Cui , Xingyu Chen , Zeyang Liu , Xuguang Lan

Industrial 3D face assets creation typically reconstructs topology-consistent face meshes from multi-view images for downstream production. However, high-quality reconstruction usually requires manual processing or specific capture…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Yating Wang , Ran Yi , Xiaoning Lei , Ke Fan , Jinkun Hao , Lizhuang Ma

We present a lightweight two-stage framework for joint geometry and color inpainting of damaged 3D objects, motivated by the digital restoration of cultural heritage artifacts. The pipeline separates damage localization from reconstruction.…

Computer Vision and Pattern Recognition · Computer Science 2026-01-05 Aarya Sumuk

We are working towards 3D reconstruction of indoor spaces using a pair of HDR cameras in a stereo vision configuration mounted on an indoor mobile floor robot that captures various textures and spatial features as 2D images and this data is…

Computer Vision and Pattern Recognition · Computer Science 2023-06-13 Kshitij Karnawat , Hritvik Choudhari , Abhimanyu Saxena , Mudit Singal , Raajith Gadam

We propose a modular framework for single-view indoor scene 3D reconstruction, where several core modules are powered by diffusion techniques. Traditional approaches for this task often struggle with the complex instance shapes and…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Yuxiao Li

We devise a graph attention network-based approach for learning a scene triangle mesh representation in order to estimate an image camera position in a dynamic environment. Previous approaches built a scene-dependent model that explicitly…

Computer Vision and Pattern Recognition · Computer Science 2022-10-03 Mohamed Amine Ouali , Mohamed Bouguessa , Riadh Ksantini

This paper demonstrates a self-supervised framework for learning voxel-wise coarse-to-fine representations tailored for dense downstream tasks. Our approach stems from the observation that existing methods for hierarchical representation…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Eytan Kats , Jochen G. Hirsch , Mattias P. Heinrich

Widespread RGB-Depth (RGB-D) sensors and advanced 3D reconstruction technologies facilitate the capture of indoor spaces, improving the fields of augmented reality (AR), virtual reality (VR), and extended reality (XR). Nevertheless, current…

Robotics · Computer Science 2026-04-22 Seok Joon Kim , Dinh Duc Cao , Federica Spinola , Se Jin Lee , Kyu Sung Cho

We present a novel method for characterizing the microstructure of a material from volumetric datasets such as 3D image data from computed tomography (CT). The method is based on a new statistical model for the distribution of voxel…

Materials Science · Physics 2021-01-06 Elise Otterlei Brenne , Vedrana Andersen Dahl , Peter Stanley Jørgensen

LiDAR is an important method for autonomous driving systems to sense the environment. The point clouds obtained by LiDAR typically exhibit sparse and irregular distribution, thus posing great challenges to the detection of 3D objects,…

Computer Vision and Pattern Recognition · Computer Science 2020-10-28 Tai Wang , Xinge Zhu , Dahua Lin

In this paper, we propose a novel LiDAR(-inertial) odometry and mapping framework to achieve the goal of simultaneous localization and meshing in real-time. This proposed framework termed ImMesh comprises four tightly-coupled modules:…

Robotics · Computer Science 2023-11-14 Jiarong Lin , Chongjiang Yuan , Yixi Cai , Haotian Li , Yunfan Ren , Yuying Zou , Xiaoping Hong , Fu Zhang

In this paper, we propose the differentiable voxelization of 3D meshes via the winding number and solid angles. The proposed approach achieves fast, flexible, and accurate voxelization of 3D meshes, admitting the computation of gradients…

Computer Vision and Pattern Recognition · Computer Science 2024-07-31 Yihao Luo , Yikai Wang , Zhengrui Xiang , Yuliang Xiu , Guang Yang , ChoonHwai Yap

In modern visual SLAM systems, it is a standard practice to retrieve potential candidate map points from overlapping keyframes for further feature matching or direct tracking. In this work, we argue that keyframes are not the optimal choice…

Robotics · Computer Science 2020-03-05 Manasi Muglikar , Zichao Zhang , Davide Scaramuzza

Recent advances on 3D object detection heavily rely on how the 3D data are represented, \emph{i.e.}, voxel-based or point-based representation. Many existing high performance 3D detectors are point-based because this structure can better…

Computer Vision and Pattern Recognition · Computer Science 2021-02-08 Jiajun Deng , Shaoshuai Shi , Peiwei Li , Wengang Zhou , Yanyong Zhang , Houqiang Li