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Neural reconstruction approaches are rapidly emerging as the preferred representation for 3D scenes, but their limited editability is still posing a challenge. In this work, we propose an approach for 3D scene inpainting -- the task of…

Computer Vision and Pattern Recognition · Computer Science 2024-04-17 Ashkan Mirzaei , Riccardo De Lutio , Seung Wook Kim , David Acuna , Jonathan Kelly , Sanja Fidler , Igor Gilitschenski , Zan Gojcic

With the popularity of monocular videos generated by video sharing and live broadcasting applications, reconstructing and editing dynamic scenes in stationary monocular cameras has become a special but anticipated technology. In contrast to…

Computer Vision and Pattern Recognition · Computer Science 2024-02-02 Weixing Xie , Xiao Dong , Yong Yang , Qiqin Lin , Jingze Chen , Junfeng Yao , Xiaohu Guo

By moving a depth sensor around a room, we compute a 3D CAD model of the environment, capturing the room shape and contents such as chairs, desks, sofas, and tables. Rather than reconstructing geometry, we match, place, and align each…

Computer Vision and Pattern Recognition · Computer Science 2020-04-08 Hamid Izadinia , Steven M. Seitz

Interactive 3D scenes are increasingly vital for embodied intelligence, yet existing datasets remain limited due to the labor-intensive process of annotating part segmentation, kinematic types, and motion trajectories. We present REACT3D, a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Zhao Huang , Boyang Sun , Alexandros Delitzas , Jiaqi Chen , Marc Pollefeys

Implicit neural representations have shown promising potential for the 3D scene reconstruction. Recent work applies it to autonomous 3D reconstruction by learning information gain for view path planning. Effective as it is, the computation…

Robotics · Computer Science 2022-09-28 Jing Zeng , Yanxu Li , Yunlong Ran , Shuo Li , Fei Gao , Lincheng Li , Shibo He , Jiming chen , Qi Ye

Multi-view implicit scene reconstruction methods have become increasingly popular due to their ability to represent complex scene details. Recent efforts have been devoted to improving the representation of input information and to reducing…

Computer Vision and Pattern Recognition · Computer Science 2022-10-04 Edward J. Smith , Michal Drozdzal , Derek Nowrouzezahrai , David Meger , Adriana Romero-Soriano

Reconstructing dynamic 4D scenes is an important yet challenging task. While 3D foundation models like VGGT excel in static settings, they often struggle with dynamic sequences where motion causes significant geometric ambiguity. To address…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Ying Zang , Yidong Han , Chaotao Ding , Yuanqi Hu , Deyi Ji , Qi Zhu , Xuanfu Li , Jin Ma , Lingyun Sun , Tianrun Chen , Lanyun Zhu

We tackle the problem of automatically reconstructing a complete 3D model of a scene from a single RGB image. This challenging task requires inferring the shape of both visible and occluded surfaces. Our approach utilizes viewer-centered,…

Computer Vision and Pattern Recognition · Computer Science 2019-08-28 Daeyun Shin , Zhile Ren , Erik B. Sudderth , Charless C. Fowlkes

Existing shape estimation methods for deformable object manipulation suffer from the drawbacks of being off-line, model dependent, noise-sensitive or occlusion-sensitive, and thus are not appropriate for manipulation tasks requiring high…

Robotics · Computer Science 2018-09-27 Tao Han , Xuan Zhao , Peigen Sun , Jia Pan

In addition to color and textural information, geometry provides important cues for 3D scene reconstruction. However, current reconstruction methods only include geometry at the feature level thus not fully exploiting the geometric…

Computer Vision and Pattern Recognition · Computer Science 2024-08-29 Ruihong Yin , Sezer Karaoglu , Theo Gevers

We present an efficient and automatic approach for accurate reconstruction of instances of big 3D objects from multiple, unorganized and unstructured point clouds, in presence of dynamic clutter and occlusions. In contrast to conventional…

Computer Vision and Pattern Recognition · Computer Science 2017-08-18 Tolga Birdal , Slobodan Ilic

3D reconstruction has been widely used in autonomous navigation fields of mobile robotics. However, the former research can only provide the basic geometry structure without the capability of open-world scene understanding, limiting…

Computer Vision and Pattern Recognition · Computer Science 2024-08-12 Haochen Jiang , Yueming Xu , Yihan Zeng , Hang Xu , Wei Zhang , Jianfeng Feng , Li Zhang

Reconstructing models of the real world, including 3D geometry, appearance, and motion of real scenes, is essential for computer graphics and computer vision. It enables the synthesizing of photorealistic novel views, useful for the movie…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Raza Yunus , Jan Eric Lenssen , Michael Niemeyer , Yiyi Liao , Christian Rupprecht , Christian Theobalt , Gerard Pons-Moll , Jia-Bin Huang , Vladislav Golyanik , Eddy Ilg

This work presents a flexible system to reconstruct 3D models of objects captured with an RGB-D sensor. A major advantage of the method is that our reconstruction pipeline allows the user to acquire a full 3D model of the object. This is…

Computer Vision and Pattern Recognition · Computer Science 2015-05-22 Aitor Aldoma , Johann Prankl , Alexander Svejda , Markus Vincze

Visual scenes are composed of visual concepts and have the property of combinatorial explosion. An important reason for humans to efficiently learn from diverse visual scenes is the ability of compositional perception, and it is desirable…

Machine Learning · Computer Science 2023-06-16 Jinyang Yuan , Tonglin Chen , Bin Li , Xiangyang Xue

We introduce Structured 3D Features, a model based on a novel implicit 3D representation that pools pixel-aligned image features onto dense 3D points sampled from a parametric, statistical human mesh surface. The 3D points have associated…

Computer Vision and Pattern Recognition · Computer Science 2023-04-18 Enric Corona , Mihai Zanfir , Thiemo Alldieck , Eduard Gabriel Bazavan , Andrei Zanfir , Cristian Sminchisescu

We present Recurrent Fitting (ReFit), a neural network architecture for single-image, parametric 3D human reconstruction. ReFit learns a feedback-update loop that mirrors the strategy of solving an inverse problem through optimization. At…

Computer Vision and Pattern Recognition · Computer Science 2023-08-23 Yufu Wang , Kostas Daniilidis

Single-view 3D shape reconstruction is an important but challenging problem, mainly for two reasons. First, as shape annotation is very expensive to acquire, current methods rely on synthetic data, in which ground-truth 3D annotation is…

Computer Vision and Pattern Recognition · Computer Science 2019-08-27 Pedro O. Pinheiro , Negar Rostamzadeh , Sungjin Ahn

Motivated by the growing demand for interactive environments, we propose an accurate real-time 3D shape reconstruction technique. To provide a reliable 3D reconstruction which is still a challenging task when dealing with real-world…

Computer Vision and Pattern Recognition · Computer Science 2018-02-20 Maryam Khanian , Ali Sharifi Boroujerdi , Michael Breuss

Recovering the shape and appearance of real-world objects from natural 2D images is a long-standing and challenging inverse rendering problem. In this paper, we introduce a novel hybrid differentiable rendering method to efficiently…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Xiangyang Zhu , Yiling Pan , Bailin Deng , Bin Wang