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3D scene generation is a core technology for gaming, film/VFX, and VR/AR. Growing demand for rapid iteration, high-fidelity detail, and accessible content creation has further increased interest in this area. Existing methods broadly follow…

Computer Vision and Pattern Recognition · Computer Science 2026-01-29 Haozhi Zhu , Miaomiao Zhao , Dingyao Liu , Runze Tian , Yan Zhang , Jie Guo , Fenggen Yu

The efficient rendering and explicit nature of 3DGS promote the advancement of 3D scene manipulation. However, existing methods typically encounter challenges in controlling the manipulation region and are unable to furnish the user with…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Yian Zhao , Wanshi Xu , Ruochong Zheng , Pengchong Qiao , Chang Liu , Jie Chen

Recent advancements in text-to-3D generation have significantly contributed to the automation and democratization of 3D content creation. Building upon these developments, we aim to address the limitations of current methods in blending…

Computer Vision and Pattern Recognition · Computer Science 2024-08-26 Yeongtak Oh , Jooyoung Choi , Yongsung Kim , Minjun Park , Chaehun Shin , Sungroh Yoon

Recent advancements in 3D object generation using diffusion models have achieved remarkable success, but generating realistic 3D urban scenes remains challenging. Existing methods relying solely on 3D diffusion models tend to suffer a…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Hanlei Guo , Jiahao Shao , Xinya Chen , Xiyang Tan , Sheng Miao , Yujun Shen , Yiyi Liao

Generating 3D worlds from text is a highly anticipated goal in computer vision. Existing works are limited by the degree of exploration they allow inside of a scene, i.e., produce streched-out and noisy artifacts when moving beyond central…

Computer Vision and Pattern Recognition · Computer Science 2025-09-17 Manuel-Andreas Schneider , Lukas Höllein , Matthias Nießner

We target a 3D generative model for general natural scenes that are typically unique and intricate. Lacking the necessary volumes of training data, along with the difficulties of having ad hoc designs in presence of varying scene…

Graphics · Computer Science 2023-04-27 Weiyu Li , Xuelin Chen , Jue Wang , Baoquan Chen

We are living in a flourishing era of digital media, where everyone has the potential to become a personal filmmaker. Current research on video generation suggests a promising avenue for controllable film creation in pixel space using…

Computer Vision and Pattern Recognition · Computer Science 2025-07-03 Weiliang Chen , Fangfu Liu , Diankun Wu , Haowen Sun , Jiwen Lu , Yueqi Duan

We introduce Scan2Mesh, a novel data-driven generative approach which transforms an unstructured and potentially incomplete range scan into a structured 3D mesh representation. The main contribution of this work is a generative neural…

Computer Vision and Pattern Recognition · Computer Science 2019-04-03 Angela Dai , Matthias Nießner

The techniques for 3D indoor scene capturing are widely used, but the meshes produced leave much to be desired. In this paper, we propose "RoomDreamer", which leverages powerful natural language to synthesize a new room with a different…

Computer Vision and Pattern Recognition · Computer Science 2023-05-22 Liangchen Song , Liangliang Cao , Hongyu Xu , Kai Kang , Feng Tang , Junsong Yuan , Yang Zhao

We present Text2Room, a method for generating room-scale textured 3D meshes from a given text prompt as input. To this end, we leverage pre-trained 2D text-to-image models to synthesize a sequence of images from different poses. In order to…

Computer Vision and Pattern Recognition · Computer Science 2023-09-12 Lukas Höllein , Ang Cao , Andrew Owens , Justin Johnson , Matthias Nießner

Synthesizing human motions in 3D environments, particularly those with complex activities such as locomotion, hand-reaching, and human-object interaction, presents substantial demands for user-defined waypoints and stage transitions. These…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Nan Jiang , Zimo He , Zi Wang , Hongjie Li , Yixin Chen , Siyuan Huang , Yixin Zhu

In recent years, significant advancements have been made in text-driven 3D content generation. However, several challenges remain. In practical applications, users often provide extremely simple text inputs while expecting high-quality 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Huiqi Wu , Jianbo Mei , Yingjie Huang , Yining Xu , Jingjiao You , Yilong Liu , Li Yao

We present a physics-based character control framework for synthesizing human-scene interactions. Recent advances adopt physics simulation to mitigate artifacts produced by data-driven kinematic approaches. However, existing physics-based…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Liang Pan , Jingbo Wang , Buzhen Huang , Junyu Zhang , Haofan Wang , Xu Tang , Yangang Wang

We introduce InseRF, a novel method for generative object insertion in the NeRF reconstructions of 3D scenes. Based on a user-provided textual description and a 2D bounding box in a reference viewpoint, InseRF generates new objects in 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-01-11 Mohamad Shahbazi , Liesbeth Claessens , Michael Niemeyer , Edo Collins , Alessio Tonioni , Luc Van Gool , Federico Tombari

We present Playable Environments - a new representation for interactive video generation and manipulation in space and time. With a single image at inference time, our novel framework allows the user to move objects in 3D while generating a…

Computer Vision and Pattern Recognition · Computer Science 2022-03-17 Willi Menapace , Stéphane Lathuilière , Aliaksandr Siarohin , Christian Theobalt , Sergey Tulyakov , Vladislav Golyanik , Elisa Ricci

This paper presents a novel method for generating diverse 3D human poses in scenes with semantic control. Existing methods heavily rely on the human-scene interaction dataset, resulting in a limited diversity of the generated human poses.…

Computer Vision and Pattern Recognition · Computer Science 2024-06-11 Bowen Dang , Xi Zhao

3D indoor scenes are widely used in computer graphics, with applications ranging from interior design to gaming to virtual and augmented reality. They also contain rich information, including room layout, as well as furniture type,…

Graphics · Computer Science 2023-02-22 Lin Gao , Jia-Mu Sun , Kaichun Mo , Yu-Kun Lai , Leonidas J. Guibas , Jie Yang

Text-driven 3D scene generation has seen significant advancements recently. However, most existing methods generate single-view images using generative models and then stitch them together in 3D space. This independent generation for each…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Wenrui Li , Fucheng Cai , Yapeng Mi , Zhe Yang , Wangmeng Zuo , Xingtao Wang , Xiaopeng Fan

Simulation is crucial for developing and evaluating autonomous vehicle (AV) systems. Recent literature builds on a new generation of generative models to synthesize highly realistic images for full-stack simulation. However, purely…

Computer Vision and Pattern Recognition · Computer Science 2025-06-25 Zehao Zhu , Yuliang Zou , Chiyu Max Jiang , Bo Sun , Vincent Casser , Xiukun Huang , Jiahao Wang , Zhenpei Yang , Ruiqi Gao , Leonidas Guibas , Mingxing Tan , Dragomir Anguelov

Text-to-image diffusion generative models can generate high quality images at the cost of tedious prompt engineering. Controllability can be improved by introducing layout conditioning, however existing methods lack layout editing ability…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Alessandro Fontanella , Petru-Daniel Tudosiu , Yongxin Yang , Shifeng Zhang , Sarah Parisot
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