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The controllability of 3D object generation methods is achieved through input text. Existing text-to-3D object generation methods primarily focus on generating a single object based on a single object description. However, these methods…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Shaorong Sun , Shuchao Pang , Yazhou Yao , Xiaoshui Huang

Text-to-image models are showcasing the impressive ability to create high-quality and diverse generative images. Nevertheless, the transition from freehand sketches to complex scene images remains challenging using diffusion models. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-07-10 Tianyu Zhang , Xiaoxuan Xie , Xusheng Du , Haoran Xie

Text-driven 3D indoor scene generation holds broad applications, ranging from gaming and smart homes to AR/VR applications. Fast and high-fidelity scene generation is paramount for ensuring user-friendly experiences. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2024-05-10 Yikun Ma , Dandan Zhan , Zhi Jin

Designing complex 3D scenes has been a tedious, manual process requiring domain expertise. Emerging text-to-3D generative models show great promise for making this task more intuitive, but existing approaches are limited to object-level…

Computer Vision and Pattern Recognition · Computer Science 2023-03-24 Ryan Po , Gordon Wetzstein

Language-guided scene-aware human motion generation has great significance for entertainment and robotics. In response to the limitations of existing datasets, we introduce LaserHuman, a pioneering dataset engineered to revolutionize…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 Peishan Cong , Ziyi Wang , Zhiyang Dou , Yiming Ren , Wei Yin , Kai Cheng , Yujing Sun , Xiaoxiao Long , Xinge Zhu , Yuexin Ma

3D scene understanding has gained significant attention due to its wide range of applications. However, existing methods for 3D scene understanding are limited to specific downstream tasks, which hinders their practicality in real-world…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Zehan Wang , Haifeng Huang , Yang Zhao , Ziang Zhang , Zhou Zhao

Diffusion models are advancing autonomous driving by enabling realistic data synthesis, predictive end-to-end planning, and closed-loop simulation, with a primary focus on temporally consistent generation. However, large-scale 3D scene…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Yu Yang , Alan Liang , Jianbiao Mei , Yukai Ma , Yong Liu , Gim Hee Lee

The scarcity of data depicting dangerous situations presents a major obstacle to training AI systems for safety-critical applications, such as construction safety, where ethical and logistical barriers hinder real-world data collection.…

Artificial Intelligence · Computer Science 2025-05-21 Vu Dinh Xuan , Hao Vo , David Murphy , Hoang D. Nguyen

The visual world we sense, interpret and interact everyday is a complex composition of interleaved physical entities. Therefore, it is a very challenging task to generate vivid scenes of similar complexity using computers. In this work, we…

Computer Vision and Pattern Recognition · Computer Science 2019-02-05 Mehmet Ozgur Turkoglu , William Thong , Luuk Spreeuwers , Berkay Kicanaoglu

GitHub Copilot is an artificial intelligence model for automatically generating source code from natural language problem descriptions. Since June 2022, Copilot has officially been available for free to all students as a plug-in to…

Human-Computer Interaction · Computer Science 2022-10-28 Paul Denny , Viraj Kumar , Nasser Giacaman

Generating coherent long-form video sequences from discrete text prompts remains challenging due to difficulties in maintaining temporal coherence, semantic consistency, and scene-action continuity across segments. We propose a novel…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Taewon Kang , Divya Kothandaraman , Ming C. Lin

3D content generation has recently attracted significant research interest, driven by its critical applications in VR/AR and embodied AI. In this work, we tackle the challenging task of synthesizing multiple 3D assets within a single scene…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 Yanxu Meng , Haoning Wu , Ya Zhang , Weidi Xie

Recent advances in Multimodal Large Language Models (MLLMs) and diffusion-based generative models have substantially improved prompt-driven image editing. However, scene text editing remains challenging, as it requires models to precisely…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Yiheng Lin , Siyu Jiao , Xiaohan Lan , Wei Zhou , Qi She , Fei Yu , Heyun Chen , Zhengwei Wang , Jinghuan Chen , Moran Li , Yingchen Yu , Zijian Feng , Yao Zhao , Yunchao Wei , Yujie Zhong

Graphics design is important for various applications, including movie production and game design. To create a high-quality scene, designers usually need to spend hours in software like Blender, in which they might need to interleave and…

Computer Vision and Pattern Recognition · Computer Science 2024-08-06 Ian Huang , Guandao Yang , Leonidas Guibas

Compositional 3D scene synthesis has diverse applications across a spectrum of industries such as robotics, films, and video games, as it closely mirrors the complexity of real-world multi-object environments. Conventional works typically…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Yao Wei , Martin Renqiang Min , George Vosselman , Li Erran Li , Michael Ying Yang

Scene-consistent video generation aims to create videos that explore 3D scenes based on a camera trajectory. Previous methods rely on video generation models with external memory for consistency, or iterative 3D reconstruction and…

Computer Vision and Pattern Recognition · Computer Science 2026-02-26 JiaKui Hu , Jialun Liu , Liying Yang , Xinliang Zhang , Kaiwen Li , Shuang Zeng , Yuanwei Li , Haibin Huang , Chi Zhang , Yanye Lu

3D scene generation is in high demand across various domains, including virtual reality, gaming, and the film industry. Owing to the powerful generative capabilities of text-to-image diffusion models that provide reliable priors, the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Haiyang Zhou , Xinhua Cheng , Wangbo Yu , Yonghong Tian , Li Yuan

Many compelling video processing effects can be achieved if per-pixel depth information and 3D camera calibrations are known. However, the success of such methods is highly dependent on the accuracy of this "scene-space" information. We…

Computer Vision and Pattern Recognition · Computer Science 2021-02-08 Felix Klose , Oliver Wang , Jean-Charles Bazin , Marcus Magnor , Alexander Sorkine-Hornung

Scene graph generation provides a compact structured representation for visual perception, but accurate and fast graph prediction from images and videos remains challenging. Recent VLM-based methods can generate scene graphs end-to-end as…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Vladislav Makarov , Mark Gizetdinov , Dmitry Yudin

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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