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We present a novel diffusion-based approach for coherent 3D scene reconstruction from a single RGB image. Our method utilizes an image-conditioned 3D scene diffusion model to simultaneously denoise the 3D poses and geometries of all objects…

Computer Vision and Pattern Recognition · Computer Science 2024-12-16 Manuel Dahnert , Angela Dai , Norman Müller , Matthias Nießner

Given an image of a natural scene, we are able to quickly decompose it into a set of components such as objects, lighting, shadows, and foreground. We can then envision a scene where we combine certain components with those from other…

Computer Vision and Pattern Recognition · Computer Science 2024-06-28 Jocelin Su , Nan Liu , Yanbo Wang , Joshua B. Tenenbaum , Yilun Du

The availability of high-speed 3D video sensors has greatly facilitated 3D shape acquisition of dynamic and deformable objects, but high frame rate 3D reconstruction is always degraded by spatial noise and temporal fluctuations. This paper…

Computer Vision and Pattern Recognition · Computer Science 2017-08-08 Jie Zhang , Christos Maniatis , Luis Horna , Robert B. Fisher

Despite significant advances in modeling image priors via diffusion models, 3D-aware image editing remains challenging, in part because the object is only specified via a single image. To tackle this challenge, we propose 3D-Fixup, a new…

Computer Vision and Pattern Recognition · Computer Science 2025-05-16 Yen-Chi Cheng , Krishna Kumar Singh , Jae Shin Yoon , Alex Schwing , Liangyan Gui , Matheus Gadelha , Paul Guerrero , Nanxuan Zhao

Efficiently reconstructing 3D scenes from monocular video remains a core challenge in computer vision, vital for applications in virtual reality, robotics, and scene understanding. Recently, frame-by-frame progressive reconstruction without…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Wenyan Cong , Hanqing Zhu , Kevin Wang , Jiahui Lei , Colton Stearns , Yuanhao Cai , Leonidas Guibas , Zhangyang Wang , Zhiwen Fan

Recognizing and generating object-state compositions has been a challenging task, especially when generalizing to unseen compositions. In this paper, we study the task of cutting objects in different styles and the resulting object state…

Computer Vision and Pattern Recognition · Computer Science 2023-09-26 Nirat Saini , Hanyu Wang , Archana Swaminathan , Vinoj Jayasundara , Bo He , Kamal Gupta , Abhinav Shrivastava

Recent progress in image and video synthesis has inspired their use in advancing 3D scene generation. However, we observe that text-to-image and -video approaches struggle to maintain scene- and object-level consistency beyond a limited…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Manuel-Andreas Schneider , Angela Dai

Reconstructing a renderable 3D model from images is a useful but challenging task. Recent feedforward 3D reconstruction methods have demonstrated remarkable success in efficiently recovering geometry, but still cannot accurately model the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Zekai Gu , Shuoxuan Feng , Yansong Wang , Hanzhuo Huang , Zhongshuo Du , Chengfeng Zhao , Chengwei Ren , Peng Wang , Yuan Liu

The accurate reconstruction of dynamic street scenes is critical for applications in autonomous driving, augmented reality, and virtual reality. Traditional methods relying on dense point clouds and triangular meshes struggle with moving…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Peizhen Zheng , Dongjing Jiang , Qingchong Jiao , Redouane EL Bouchtaoui , Flynnwell Jianfei Zhang

We present an algorithm that produces a plan for relocating obstacles in order to grasp a target in clutter by a robotic manipulator without collisions. We consider configurations where objects are densely populated in a constrained and…

Robotics · Computer Science 2019-02-20 Jinhwi Lee , Younggil Cho , Changjoo Nam , Jonghyeon Park , Changhwan Kim

We present ShapeClipper, a novel method that reconstructs 3D object shapes from real-world single-view RGB images. Instead of relying on laborious 3D, multi-view or camera pose annotation, ShapeClipper learns shape reconstruction from a set…

Computer Vision and Pattern Recognition · Computer Science 2023-04-14 Zixuan Huang , Varun Jampani , Anh Thai , Yuanzhen Li , Stefan Stojanov , James M. Rehg

Reconstructing an accurate 3D object model from a few image observations remains a challenging problem in computer vision. State-of-the-art approaches typically assume accurate camera poses as input, which could be difficult to obtain in…

Computer Vision and Pattern Recognition · Computer Science 2022-05-17 Zhenpei Yang , Zhile Ren , Miguel Angel Bautista , Zaiwei Zhang , Qi Shan , Qixing Huang

Video diffusion models generate high-quality and diverse worlds; however, individual frames often lack 3D consistency across the output sequence, which makes the reconstruction of 3D worlds difficult. To this end, we propose a new method…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Lukas Höllein , Matthias Nießner

This paper investigates an open research challenge of reconstructing high-quality, large 3D open scenes from images. It is observed existing methods have various limitations, such as requiring precise camera poses for input and dense…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Chong Cheng , Gaochao Song , Yiyang Yao , Qinzheng Zhou , Gangjian Zhang , Hao Wang

Generative video modeling has emerged as a compelling tool to zero-shot reason about plausible physical interactions for open-world manipulation. Yet, it remains a challenge to translate such human-led motions into the low-level actions…

Robotics · Computer Science 2026-01-01 Karthik Dharmarajan , Wenlong Huang , Jiajun Wu , Li Fei-Fei , Ruohan Zhang

Recent text-to-image models have revolutionized image generation, but they still struggle with maintaining concept consistency across generated images. While existing works focus on character consistency, they often overlook the crucial…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Quanjian Song , Donghao Zhou , Jingyu Lin , Fei Shen , Jiaze Wang , Xiaowei Hu , Cunjian Chen , Pheng-Ann Heng

Open-vocabulary 3D scene understanding enables users to segment novel objects in complex 3D environments through natural language. However, existing approaches remain slow, memory-intensive, and overly complex due to iterative optimization…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Jaehun Bang , Jinhyeok Kim , Minji Kim , Seungheon Jeong , Kyungdon Joo

In recent years, numerous ideas have emerged for designing a mutually reinforcing mechanism or extra stages for the image fusion task, ignoring the inevitable gaps between different vision tasks and the computational burden. We argue that…

Computer Vision and Pattern Recognition · Computer Science 2024-02-09 Chunyang Cheng , Tianyang Xu , Xiao-Jun Wu , Hui Li , Xi Li , Josef Kittler

Volumetric models have become a popular representation for 3D scenes in recent years. One breakthrough leading to their popularity was KinectFusion, which focuses on 3D reconstruction using RGB-D sensors. However, monocular SLAM has since…

Computer Vision and Pattern Recognition · Computer Science 2017-08-03 Victor Adrian Prisacariu , Olaf Kähler , Stuart Golodetz , Michael Sapienza , Tommaso Cavallari , Philip H S Torr , David W Murray

While Structure from Motion (SfM) achieves great success in 3D reconstruction, it still meets challenges on large scale scenes. In this work, large scale SfM is deemed as a graph problem, and we tackle it in a divide-and-conquer manner.…

Computer Vision and Pattern Recognition · Computer Science 2020-06-09 Yu Chen , Shuhan Shen , Yisong Chen , Guoping Wang
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