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With the development of deep neural networks, the demand for a significant amount of annotated training data becomes the performance bottlenecks in many fields of research and applications. Image synthesis can generate annotated images…

Computer Vision and Pattern Recognition · Computer Science 2020-12-24 Minghui Liao , Boyu Song , Shangbang Long , Minghang He , Cong Yao , Xiang Bai

While 3D generation is progressing rapidly, recent work has often focused on obtaining high-resolution assets, leaving user experience and deployability as afterthoughts. We present AssetGen, a 3D generator that focuses instead on these two…

Recent advances in large reconstruction and generative models have significantly improved scene reconstruction and novel view generation. However, due to compute limitations, each inference with these large models is confined to a small…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Shangjin Zhai , Zhichao Ye , Jialin Liu , Weijian Xie , Jiaqi Hu , Zhen Peng , Hua Xue , Danpeng Chen , Xiaomeng Wang , Lei Yang , Nan Wang , Haomin Liu , Guofeng Zhang

The integration of Large Language Models (LLMs) like GPT-4 with Extended Reality (XR) technologies offers the potential to build truly immersive XR environments that interact with human users through natural language, e.g., generating and…

Multimedia · Computer Science 2025-03-21 Jiangong Chen , Xiaoyi Wu , Tian Lan , Bin Li

Among various interactions between humans, such as eye contact and gestures, physical interactions by contact can act as an essential moment in understanding human behaviors. Inspired by this fact, given a 3D partner human with the desired…

Computer Vision and Pattern Recognition · Computer Science 2024-02-06 Dongjun Gu , Jaehyeok Shim , Jaehoon Jang , Changwoo Kang , Kyungdon Joo

This paper explores the burgeoning field of 3D content generation within the landscape of Artificial Intelligence Generated Content (AIGC) and large-scale models. It investigates innovative methods like Text-to-3D and Image-to-3D, which…

Graphics · Computer Science 2024-05-27 Ke Zhao , Andreas Larsen

Human motion generation is a significant pursuit in generative computer vision with widespread applications in film-making, video games, AR/VR, and human-robot interaction. Current methods mainly utilize either diffusion-based generative…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Canxuan Gang

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

Agentic reinforcement learning increasingly relies on experience-driven scaling, yet real-world environments remain non-adaptive, limited in coverage, and difficult to scale. World models offer a potential way to improve learning efficiency…

Computation and Language · Computer Science 2026-03-06 Yixia Li , Hongru Wang , Jiahao Qiu , Zhenfei Yin , Dongdong Zhang , Cheng Qian , Zeping Li , Pony Ma , Guanhua Chen , Heng Ji

Recent advancements in generative models have enabled the creation of dynamic 4D content - 3D objects in motion - based on text prompts, which holds potential for applications in virtual worlds, media, and gaming. Existing methods provide…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Ohad Rahamim , Ori Malca , Dvir Samuel , Gal Chechik

While diffusion models have significantly advanced the quality of image generation their capability to accurately and coherently render text within these images remains a substantial challenge. Conventional diffusion-based methods for scene…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Qilong Zhangli , Jindong Jiang , Di Liu , Licheng Yu , Xiaoliang Dai , Ankit Ramchandani , Guan Pang , Dimitris N. Metaxas , Praveen Krishnan

Understanding 3D scenes in open-world settings poses fundamental challenges for vision and robotics, particularly due to the limitations of closed-vocabulary supervision and static annotations. To address this, we propose a unified…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Fei Yu , Quan Deng , Shengeng Tang , Yuehua Li , Lechao Cheng

With the recent development of generative models, Text-to-3D generations have also seen significant growth, opening a door for creating video-game 3D assets from a more general public. Nonetheless, people without any professional 3D editing…

Computer Vision and Pattern Recognition · Computer Science 2024-08-12 Zhaoning Wang , Ming Li , Chen Chen

By combining voice and touch interactions, multimodal interfaces can surpass the efficiency of either modality alone. Traditional multimodal frameworks require laborious developer work to support rich multimodal commands where the user's…

Human-Computer Interaction · Computer Science 2024-05-03 Jackie Junrui Yang , Yingtian Shi , Yuhan Zhang , Karina Li , Daniel Wan Rosli , Anisha Jain , Shuning Zhang , Tianshi Li , James A. Landay , Monica S. Lam

In recent years, 3D Gaussian splatting has emerged as a powerful technique for 3D reconstruction and generation, known for its fast and high-quality rendering capabilities. To address these shortcomings, this paper introduces a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Xianglong He , Junyi Chen , Sida Peng , Di Huang , Yangguang Li , Xiaoshui Huang , Chun Yuan , Wanli Ouyang , Tong He

Text-to-image (T2I) generation has made remarkable progress in producing high-quality images, but a fundamental challenge remains: creating backgrounds that naturally accommodate text placement without compromising image quality. This…

Computer Vision and Pattern Recognition · Computer Science 2025-05-14 Tianyi Liang , Jiangqi Liu , Yifei Huang , Shiqi Jiang , Jianshen Shi , Changbo Wang , Chenhui Li

Recent advances in large language models (LLMs) have significantly improved language-driven 3D content generation, but most existing approaches still treat scene generation and user interaction as separate processes, limiting the…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Anh H. Vo , Sungyo Lee , Phil-Joong Kim , Soo-Mi Choi , Yong-Guk Kim

World models that support controllable and editable spatiotemporal environments are valuable for robotics, enabling scalable training data, repro ducible evaluation, and flexible task design. While recent text-to-video models generate…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Xuehai He , Shijie Zhou , Thivyanth Venkateswaran , Kaizhi Zheng , Ziyu Wan , Achuta Kadambi , Xin Eric Wang

Modeling and generating 3D human-object interactions from text is crucial for applications in AR, XR, and gaming. Existing approaches often rely on score distillation from text-to-image models, but their results suffer from the Janus…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Agniv Sharma , Xianghui Xie , Tom Fischer , Eddy Ilg , Gerard Pons-Moll

Text-to-3D scene generation from natural language is highly desirable for digital content creation. However, existing methods are largely domain-restricted or reliant on predefined spatial relationships, limiting their capacity for…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Jun Luo , Jiaxiang Tang , Ruijie Lu , Gang Zeng