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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

In the pursuit of efficient automated content creation, procedural generation, leveraging modifiable parameters and rule-based systems, emerges as a promising approach. Nonetheless, it could be a demanding endeavor, given its intricate…

Computer Vision and Pattern Recognition · Computer Science 2024-05-30 Chunyi Sun , Junlin Han , Weijian Deng , Xinlong Wang , Zishan Qin , Stephen Gould

We propose Text2Scene, a method to automatically create realistic textures for virtual scenes composed of multiple objects. Guided by a reference image and text descriptions, our pipeline adds detailed texture on labeled 3D geometries in…

Computer Vision and Pattern Recognition · Computer Science 2023-09-01 Inwoo Hwang , Hyeonwoo Kim , Young Min Kim

In this work, we explore the challenging task of generating 3D shapes from text. Beyond the existing works, we propose a new approach for text-guided 3D shape generation, capable of producing high-fidelity shapes with colors that match the…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Zhengzhe Liu , Yi Wang , Xiaojuan Qi , Chi-Wing Fu

We present MeshLLM, a novel framework that leverages large language models (LLMs) to understand and generate text-serialized 3D meshes. Our approach addresses key limitations in existing methods, including the limited dataset scale when…

Text-to-image generation has witnessed significant progress with the advent of diffusion models. Despite the ability to generate photorealistic images, current text-to-image diffusion models still often struggle to accurately interpret and…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Tsung-Han Wu , Long Lian , Joseph E. Gonzalez , Boyi Li , Trevor Darrell

We identify occlusion reasoning as a fundamental yet overlooked aspect for 3D layout-conditioned generation. It is essential for synthesizing partially occluded objects with depth-consistent geometry and scale. While existing methods can…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Vaibhav Agrawal , Rishubh Parihar , Pradhaan Bhat , Ravi Kiran Sarvadevabhatla , R. Venkatesh Babu

Interactive video generation has significant potential for scene simulation and video creation. However, existing methods often struggle with maintaining scene consistency during long video generation under dynamic camera control due to…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Xinhang Gao , Junlin Guan , Shuhan Luo , Wenzhuo Li , Guanghuan Tan , Jiacheng Wang

The emergence of virtual reality has necessitated the generation of detailed and customizable 3D hand models for interaction in the virtual world. However, the current methods for 3D hand model generation are both expensive and cumbersome,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Green Rosh , Prateek Kukreja , Vishakha SR , Pawan Prasad B H

We propose a novel task of text-controlled human object interaction generation in 3D scenes with movable objects. Existing human-scene interaction datasets suffer from insufficient interaction categories and typically only consider…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Xinhao Cai , Minghang Zheng , Xin Jin , Yang Liu

Text-to-LiDAR generation can customize 3D data with rich structures and diverse scenes for downstream tasks. However, the scarcity of Text-LiDAR pairs often causes insufficient training priors, generating overly smooth 3D scenes. Moreover,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Wentao Qu , Guofeng Mei , Yang Wu , Yongshun Gong , Xiaoshui Huang , Liang Xiao

Generating 3D scenes from natural language holds great promise for applications in gaming, film, and design. However, existing methods struggle with automation, 3D consistency, and fine-grained control. We present DreamScene, an end-to-end…

Computer Vision and Pattern Recognition · Computer Science 2025-07-30 Haoran Li , Yuli Tian , Kun Lan , Yong Liao , Lin Wang , Pan Hui , Peng Yuan Zhou

Current methods for generating 3D scene layouts from text predominantly follow a declarative paradigm, where a Large Language Model (LLM) specifies high-level constraints that are then resolved by a separate solver. This paper challenges…

Text-guided 3D face synthesis has achieved remarkable results by leveraging text-to-image (T2I) diffusion models. However, most existing works focus solely on the direct generation, ignoring the editing, restricting them from synthesizing…

Computer Vision and Pattern Recognition · Computer Science 2023-12-04 Yunjie Wu , Yapeng Meng , Zhipeng Hu , Lincheng Li , Haoqian Wu , Kun Zhou , Weiwei Xu , Xin Yu

Current text-to-image generation models often struggle to follow textual instructions, especially the ones requiring spatial reasoning. On the other hand, Large Language Models (LLMs), such as GPT-4, have shown remarkable precision in…

Computer Vision and Pattern Recognition · Computer Science 2023-05-31 Tianjun Zhang , Yi Zhang , Vibhav Vineet , Neel Joshi , Xin Wang

3D generation from natural language offers significant potential to reduce expert manual modeling efforts and enhance accessibility to 3D assets. However, existing methods often yield unstructured meshes and exhibit poor interactivity,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Shuyuan Zhang , Chenhan Jiang , Zuoou Li , Jiankang Deng

Text-to-3D generation has recently seen significant progress. To enhance its practicality in real-world applications, it is crucial to generate multiple independent objects with interactions, similar to layer-compositing in 2D image…

Computer Vision and Pattern Recognition · Computer Science 2024-07-24 Zizheng Yan , Jiapeng Zhou , Fanpeng Meng , Yushuang Wu , Lingteng Qiu , Zisheng Ye , Shuguang Cui , Guanying Chen , Xiaoguang Han

We introduce CHOrD, a novel framework for scalable synthesis of 3D indoor scenes, designed to create house-scale, collision-free, and hierarchically structured indoor digital twins. In contrast to existing methods that directly synthesize…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Chong Su , Yingbin Fu , Zheyuan Hu , Jing Yang , Param Hanji , Shaojun Wang , Xuan Zhao , Cengiz Öztireli , Fangcheng Zhong

We introduce a method to generate 3D scenes that are disentangled into their component objects. This disentanglement is unsupervised, relying only on the knowledge of a large pretrained text-to-image model. Our key insight is that objects…

Computer Vision and Pattern Recognition · Computer Science 2024-02-28 Dave Epstein , Ben Poole , Ben Mildenhall , Alexei A. Efros , Aleksander Holynski

Recent text-to-video (T2V) generation methods have seen significant advancements. However, the majority of these works focus on producing short video clips of a single event (i.e., single-scene videos). Meanwhile, recent large language…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Han Lin , Abhay Zala , Jaemin Cho , Mohit Bansal
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