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AR/VR applications and robots need to know when the scene has changed. An example is when objects are moved, added, or removed from the scene. We propose a 3D object discovery method that is based only on scene changes. Our method does not…

Computer Vision and Pattern Recognition · Computer Science 2022-08-23 Aikaterini Adam , Torsten Sattler , Konstantinos Karantzalos , Tomas Pajdla

We present the first real-time system capable of tracking and reconstructing, individually, every visible object in a given scene, without any form of prior on the rigidness of the objects, texture existence, or object category. In contrast…

Robotics · Computer Science 2022-10-11 Haonan Chang , Abdeslam Boularias

Dynamic 3D reconstruction and point tracking in videos are typically treated as separate tasks, despite their deep connection. We propose St4RTrack, a feed-forward framework that simultaneously reconstructs and tracks dynamic video content…

Computer Vision and Pattern Recognition · Computer Science 2025-04-18 Haiwen Feng , Junyi Zhang , Qianqian Wang , Yufei Ye , Pengcheng Yu , Michael J. Black , Trevor Darrell , Angjoo Kanazawa

In multi-view human body capture systems, the recovered 3D geometry or even the acquired imagery data can be heavily corrupted due to occlusions, noise, limited field of- view, etc. Direct estimation of 3D pose, body shape or motion on…

Computer Vision and Pattern Recognition · Computer Science 2018-02-02 Zhong Li , Yu Ji , Wei Yang , Jinwei Ye , Jingyi Yu

We investigate the problem of learning category-specific 3D shape reconstruction from a variable number of RGB views of previously unobserved object instances. Most approaches for multiview shape reconstruction operate on sparse shape…

Computer Vision and Pattern Recognition · Computer Science 2019-12-10 Srinath Sridhar , Davis Rempe , Julien Valentin , Sofien Bouaziz , Leonidas J. Guibas

We propose an online object-level SLAM system which builds a persistent and accurate 3D graph map of arbitrary reconstructed objects. As an RGB-D camera browses a cluttered indoor scene, Mask-RCNN instance segmentations are used to…

Computer Vision and Pattern Recognition · Computer Science 2018-08-29 John McCormac , Ronald Clark , Michael Bloesch , Andrew J. Davison , Stefan Leutenegger

A comprehensive semantic understanding of a scene is important for many applications - but in what space should diverse semantic information (e.g., objects, scene categories, material types, texture, etc.) be grounded and what should be its…

Computer Vision and Pattern Recognition · Computer Science 2019-10-08 Iro Armeni , Zhi-Yang He , JunYoung Gwak , Amir R. Zamir , Martin Fischer , Jitendra Malik , Silvio Savarese

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

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 propose a method for 3D object reconstruction and 6D-pose estimation from 2D images that uses knowledge about object shape as the primary key. In the proposed pipeline, recognition and labeling of objects in 2D images deliver 2D segment…

Computer Vision and Pattern Recognition · Computer Science 2022-03-03 Marcell Wolnitza , Osman Kaya , Tomas Kulvicius , Florentin Wörgötter , Babette Dellen

We present a novel approach for real-time joint reconstruction of 3D scene motion and geometry from binocular stereo videos. Our approach is based on a novel variational halfway-domain scene flow formulation, which allows us to obtain…

Computer Vision and Pattern Recognition · Computer Science 2016-10-25 Lucas Thies , Michael Zollhöfer , Christian Richardt , Christian Theobalt , Günther Greiner

Reconstructing urban scenes is challenging due to their complex geometries and the presence of potentially dynamic objects. 3D Gaussian Splatting (3DGS)-based methods have shown strong performance, but existing approaches often incorporate…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Ziwen Li , Jiaxin Huang , Runnan Chen , Yunlong Che , Yandong Guo , Tongliang Liu , Fakhri Karray , Mingming Gong

Estimation of 3D motion in a dynamic scene from a temporal pair of images is a core task in many scene understanding problems. In real world applications, a dynamic scene is commonly captured by a moving camera (i.e., panning, tilting or…

Computer Vision and Pattern Recognition · Computer Science 2018-07-31 Zhaoyang Lv , Kihwan Kim , Alejandro Troccoli , Deqing Sun , James M. Rehg , Jan Kautz

Deformable 3D Gaussian Splatting (3D-GS) is limited by missing intermediate motion information due to the low temporal resolution of RGB cameras. To address this, we introduce the first approach combining event cameras, which capture…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Wenhao Xu , Wenming Weng , Yueyi Zhang , Ruikang Xu , Zhiwei Xiong

This paper studies the problem of 3D volumetric reconstruction from two views of a scene with an unknown camera. While seemingly easy for humans, this problem poses many challenges for computers since it requires simultaneously…

Computer Vision and Pattern Recognition · Computer Science 2020-07-28 Shengyi Qian , Linyi Jin , David F. Fouhey

In this paper, we study the problem of 3D scene geometry decomposition and manipulation from 2D views. By leveraging the recent implicit neural representation techniques, particularly the appealing neural radiance fields, we introduce an…

Computer Vision and Pattern Recognition · Computer Science 2023-03-13 Bing Wang , Lu Chen , Bo Yang

Change detection plays a vital role in scene monitoring, exploration, and continual reconstruction. Existing 3D change detection methods often exhibit spatial inconsistency in the detected changes and fail to explicitly separate pre- and…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Zirui Zhou , Junfeng Ni , Shujie Zhang , Yixin Chen , Siyuan Huang

Sensing the medical scenario can ensure the safety during the surgical operations. So, in this regard, a monitor platform which can obtain the accurate location information of the surgery room is desperately needed. Compared to 2D camera…

Computer Vision and Pattern Recognition · Computer Science 2018-09-06 Ke Wang , Han Song , Jiahui Zhang , Xinran Zhang , Hongen Liao

Recently, the generation of dynamic 3D objects from a video has shown impressive results. Existing methods directly optimize Gaussians using whole information in frames. However, when dynamic regions are interwoven with static regions…

Computer Vision and Pattern Recognition · Computer Science 2025-06-30 Liying Yang , Chen Liu , Zhenwei Zhu , Ajian Liu , Hui Ma , Jian Nong , Yanyan Liang

Learning non-rigid registration in an end-to-end manner is challenging due to the inherent high degrees of freedom and the lack of labeled training data. In this paper, we resolve these two challenges simultaneously. First, we propose to…

Computer Vision and Pattern Recognition · Computer Science 2021-04-14 Wanquan Feng , Juyong Zhang , Hongrui Cai , Haofei Xu , Junhui Hou , Hujun Bao