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Existing single-image 3D indoor scene generators often produce results that look visually plausible but fail to obey real-world physics, limiting their reliability in robotics, embodied AI, and design. To examine this gap, we introduce a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Dongli Wu , Jingyu Hu , Ka-Hei Hui , Xiaobao Wei , Chengwen Luo , Jianqiang Li , Zhengzhe Liu

Creating machines capable of understanding the world in 3D is essential in assisting designers that build and edit 3D environments and robots navigating and interacting within a three-dimensional space. Inspired by advances in language and…

Computer Vision and Pattern Recognition · Computer Science 2026-01-07 Aadarsh Sahoo , Vansh Tibrewal , Georgia Gkioxari

The creation of high-fidelity, customizable 3D indoor scene textures remains a significant challenge. While text-driven methods offer flexibility, they lack the precision for fine-grained, instance-level control, and often produce textures…

Computer Vision and Pattern Recognition · Computer Science 2026-03-23 Weilin Chen , Jiahao Rao , Wenhao Wang , Xinyang Li , Xuan Cheng , Liujuan Cao

Despite enormous progress in object detection and classification, the problem of incorporating expected contextual relationships among object instances into modern recognition systems remains a key challenge. In this work we propose…

Computer Vision and Pattern Recognition · Computer Science 2017-01-11 Ehsan Jahangiri , Erdem Yoruk , Rene Vidal , Laurent Younes , Donald Geman

3D scene reconstruction from 2D images has been a long-standing task. Instead of estimating per-frame depth maps and fusing them in 3D, recent research leverages the neural implicit surface as a unified representation for 3D reconstruction.…

Computer Vision and Pattern Recognition · Computer Science 2023-09-19 Xinyi Yu , Liqin Lu , Jintao Rong , Guangkai Xu , Linlin Ou

Robotic tasks such as planning and navigation require a hierarchical semantic understanding of a scene, which could include multiple floors and rooms. Current methods primarily focus on object segmentation for 3D scene understanding.…

Computer Vision and Pattern Recognition · Computer Science 2024-12-13 Yash Mehan , Kumaraditya Gupta , Rohit Jayanti , Anirudh Govil , Sourav Garg , Madhava Krishna

We study the problem of synthesizing immersive 3D indoor scenes from one or more images. Our aim is to generate high-resolution images and videos from novel viewpoints, including viewpoints that extrapolate far beyond the input images while…

Computer Vision and Pattern Recognition · Computer Science 2022-12-02 Jing Yu Koh , Harsh Agrawal , Dhruv Batra , Richard Tucker , Austin Waters , Honglak Lee , Yinfei Yang , Jason Baldridge , Peter Anderson

Recent conditional image synthesis approaches provide high-quality synthesized images. However, it is still challenging to accurately adjust image contents such as the positions and orientations of objects, and synthesized images often have…

Computer Vision and Pattern Recognition · Computer Science 2021-08-25 Jaebong Jeong , Janghun Jo , Jingdong Wang , Sunghyun Cho , Jaesik Park

Designing 3D scenes is currently a creative task that requires significant expertise and effort in using complex 3D design interfaces. This effortful design process starts in stark contrast to the easiness with which people can use language…

Graphics · Computer Science 2017-03-02 Angel X. Chang , Mihail Eric , Manolis Savva , Christopher D. Manning

Computer-aided design (CAD) tools empower designers to design and modify 3D models through a series of CAD operations, commonly referred to as a CAD sequence. In scenarios where digital CAD files are not accessible, reverse engineering (RE)…

Computer Vision and Pattern Recognition · Computer Science 2025-01-10 Xingang Li , Zhenghui Sha

Autonomous 3D indoor scene synthesis breaks down in non-convex rooms with tightly coupled spatial constraints. Data-driven generators lack topological priors for long-horizon planning, while iterative agents fragment semantics and become…

Robotics · Computer Science 2026-05-05 Meisheng Zhang , Shizhao Sun , Yang Zhao , Ziyuan Liu , Zhijun Gao , Jiang Bian

Research into dynamic 3D scene understanding has primarily focused on short-term change tracking from dense observations, while little attention has been paid to long-term changes with sparse observations. We address this gap with MoRE, a…

Computer Vision and Pattern Recognition · Computer Science 2024-03-28 Liyuan Zhu , Shengyu Huang , Konrad Schindler , Iro Armeni

We present a method for creating 3D indoor scenes with a generative model learned from a collection of semantic-segmented depth images captured from different unknown scenes. Given a room with a specified size, our method automatically…

Computer Vision and Pattern Recognition · Computer Science 2021-08-23 Ming-Jia Yang , Yu-Xiao Guo , Bin Zhou , Xin Tong

Semantic Scene Completion aims at reconstructing a complete 3D scene with precise voxel-wise semantics from a single-view depth or RGBD image. It is a crucial but challenging problem for indoor scene understanding. In this work, we present…

Computer Vision and Pattern Recognition · Computer Science 2021-06-08 Yingjie Cai , Xuesong Chen , Chao Zhang , Kwan-Yee Lin , Xiaogang Wang , Hongsheng Li

We present SceneNAT, a single-stage masked non-autoregressive Transformer that synthesizes complete 3D indoor scenes from natural language instructions through only a few parallel decoding passes, offering improved performance and…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Jeongjun Choi , Yeonsoo Park , H. Jin Kim

Controllable 3D indoor scene synthesis stands at the forefront of technological progress, offering various applications like gaming, film, and augmented/virtual reality. The capability to stylize and de-couple objects within these scenarios…

Computer Vision and Pattern Recognition · Computer Science 2024-01-25 Yunfan Zhang , Hong Huang , Zhiwei Xiong , Zhiqi Shen , Guosheng Lin , Hao Wang , Nicholas Vun

In this work we propose a deep learning pipeline to predict the visual future appearance of an urban scene. Despite recent advances, generating the entire scene in an end-to-end fashion is still far from being achieved. Instead, here we…

Computer Vision and Pattern Recognition · Computer Science 2021-10-25 Alessandro Simoni , Luca Bergamini , Andrea Palazzi , Simone Calderara , Rita Cucchiara

Simulation of forest environments has applications from entertainment and art creation to commercial and scientific modelling. Due to the unique features and lighting in forests, a forest-specific simulator is desirable, however many…

Graphics · Computer Science 2022-08-03 Callum Newlands , Klaus-Peter Zauner

The reconstruction of immersive and realistic 3D scenes holds significant practical importance in various fields of computer vision and computer graphics. Typically, immersive and realistic scenes should be free from obstructions by dynamic…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Zilong Huang , Jun He , Junyan Ye , Lihan Jiang , Weijia Li , Yiping Chen , Ting Han

This paper presents SceneCut, a novel approach to jointly discover previously unseen objects and non-object surfaces using a single RGB-D image. SceneCut's joint reasoning over scene semantics and geometry allows a robot to detect and…

Computer Vision and Pattern Recognition · Computer Science 2018-05-25 Trung Pham , Thanh-Toan Do , Niko Sünderhauf , Ian Reid
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