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Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Shengqu Cai , Duygu Ceylan , Matheus Gadelha , Chun-Hao Paul Huang , Tuanfeng Yang Wang , Gordon Wetzstein

Generating controllable and physically plausible indoor scenes is a pivotal prerequisite for constructing high-fidelity simulation environments for embodied AI. However, existing deeplearning-based methods usually treat all objects as…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Zini Chen , Junming Huang , Rong Zhang , Jiamin Xu , Cheng Peng , Chi Wang , Weiwei Xu

Controllability, temporal coherence, and detail synthesis remain the most critical challenges in video generation. In this paper, we focus on a commonly used yet underexplored cinematic technique known as Frame In and Frame Out.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-27 Boyang Wang , Xuweiyi Chen , Matheus Gadelha , Zezhou Cheng

In recent years, 3D scene graphs have emerged as a powerful world representation, offering both geometric accuracy and semantic richness. Combining 3D scene graphs with large language models enables robots to reason, plan, and navigate in…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Abdelrhman Werby , Dennis Rotondi , Fabio Scaparro , Kai O. Arras

We introduce ClutterGen, a physically compliant simulation scene generator capable of producing highly diverse, cluttered, and stable scenes for robot learning. Generating such scenes is challenging as each object must adhere to physical…

Robotics · Computer Science 2024-10-08 Yinsen Jia , Boyuan Chen

Recent advances in text-to-image generation with diffusion models present transformative capabilities in image quality. However, user controllability of the generated image, and fast adaptation to new tasks still remains an open challenge,…

Computer Vision and Pattern Recognition · Computer Science 2023-02-17 Omer Bar-Tal , Lior Yariv , Yaron Lipman , Tali Dekel

This paper presents a novel approach for structure-preserving planar simplification of indoor scene point clouds for both simulated and real-world environments. Initially, the scene point cloud undergoes preprocessing steps, including noise…

Computer Vision and Pattern Recognition · Computer Science 2024-08-22 Bishwash Khanal , Sanjay Rijal , Manish Awale , Vaghawan Ojha

The modern computer graphics pipeline can synthesize images at remarkable visual quality; however, it requires well-defined, high-quality 3D content as input. In this work, we explore the use of imperfect 3D content, for instance, obtained…

Computer Vision and Pattern Recognition · Computer Science 2019-04-30 Justus Thies , Michael Zollhöfer , Matthias Nießner

Current one-pass 3D scene synthesis methods often suffer from spatial hallucinations, such as collisions, due to a lack of deliberative reasoning. To bridge this gap, we introduce SceneReVis, a vision-grounded self-reflection framework that…

Computer Vision and Pattern Recognition · Computer Science 2026-02-11 Yang Zhao , Shizhao Sun , Meisheng Zhang , Yingdong Shi , Xubo Yang , Jiang Bian

Recent breakthroughs in 3D generation have enabled the synthesis of high-fidelity individual assets. However, generating 3D compositional objects from single images--particularly under occlusions--remains challenging. Existing methods often…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Hui Shan , Keyang Luo , Ming Li , Sizhe Zheng , Yanwei Fu , Zhen Chen , Xiangru Huang

Current text-to-3D methods excel at generating single objects but falter on compositional prompts. We argue this failure is fundamental to their optimization schedules, as simultaneous or iterative heuristics predictably collapse under a…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Utkarsh Nath , Rajeev Goel , Rahul Khurana , Kyle Min , Mark Ollila , Pavan Turaga , Varun Jampani , Tejaswi Gowda

Generating 3D scenes is still a challenging task due to the lack of readily available scene data. Most existing methods only produce partial scenes and provide limited navigational freedom. We introduce a practical and scalable solution…

Graphics · Computer Science 2025-09-26 Zhaoyang Zhang , Yannick Hold-Geoffroy , Miloš Hašan , Ziwen Chen , Fujun Luan , Julie Dorsey , Yiwei Hu

Metaverse platforms are rapidly evolving to provide immersive spaces for user interaction and content creation. However, the generation of dynamic and interactive 3D objects remains challenging due to the need for advanced 3D modeling and…

Human-Computer Interaction · Computer Science 2025-05-01 Ryutaro Kurai , Takefumi Hiraki , Yuichi Hiroi , Yutaro Hirao , Monica Perusquía-Hernández , Hideaki Uchiyama , Kiyoshi Kiyokawa

Attaining a high degree of user controllability in visual generation often requires intricate, fine-grained inputs like layouts. However, such inputs impose a substantial burden on users when compared to simple text inputs. To address the…

Computer Vision and Pattern Recognition · Computer Science 2023-10-31 Weixi Feng , Wanrong Zhu , Tsu-jui Fu , Varun Jampani , Arjun Akula , Xuehai He , Sugato Basu , Xin Eric Wang , William Yang Wang

3D scene generation has garnered growing attention in recent years and has made significant progress. Generating 4D cities is more challenging than 3D scenes due to the presence of structurally complex, visually diverse objects like…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Haozhe Xie , Zhaoxi Chen , Fangzhou Hong , Ziwei Liu

Recently, the surge of efficient and automated 3D AI-generated content (AIGC) methods has increasingly illuminated the path of transforming human imagination into complex 3D structures. However, the automated generation of 3D content is…

Graphics · Computer Science 2024-12-20 Pei Chen , Fudong Wang , Yixuan Tong , Jingdong Chen , Ming Yang , Minghui Yang

Recovering high-quality 3D scenes from a single RGB image is a challenging task in computer graphics. Current methods often struggle with domain-specific limitations or low-quality object generation. To address these, we propose CAST…

Computer Vision and Pattern Recognition · Computer Science 2025-05-14 Kaixin Yao , Longwen Zhang , Xinhao Yan , Yan Zeng , Qixuan Zhang , Wei Yang , Lan Xu , Jiayuan Gu , Jingyi Yu

Single-view indoor scene generation plays a crucial role in a range of real-world applications. However, generating a complete 360{\deg} scene from a single image remains a highly ill-posed and challenging problem. Recent approaches have…

Computer Vision and Pattern Recognition · Computer Science 2026-01-27 Runmao Yao , Junsheng Zhou , Zhen Dong , Yu-Shen Liu

Automatic indoor layout generation has attracted increasing attention due to its potential in interior design, virtual environment construction, and embodied AI. Existing methods fall into two categories: prompt-driven approaches that…

Computer Vision and Pattern Recognition · Computer Science 2025-09-22 Yixuan Yang , Zhen Luo , Tongsheng Ding , Junru Lu , Mingqi Gao , Jinyu Yang , Victor Sanchez , Feng Zheng

Text-to-3D scene generation holds immense potential for the gaming, film, and architecture sectors. Despite significant progress, existing methods struggle with maintaining high quality, consistency, and editing flexibility. In this paper,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-22 Haoran Li , Haolin Shi , Wenli Zhang , Wenjun Wu , Yong Liao , Lin Wang , Lik-hang Lee , Pengyuan Zhou
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