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Related papers: MUSES: 3D-Controllable Image Generation via Multi-…

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We present MUSE, a software framework for combining existing computational tools for different astrophysical domains into a single multiphysics, multiscale application. MUSE facilitates the coupling of existing codes written in different…

Astrophysics · Physics 2009-11-13 Simon Portegies Zwart , Steve McMillan , Stefan Harfst , Derek Groen , Michiko Fujii

Despite the success in large-scale text-to-image generation and text-conditioned image editing, existing methods still struggle to produce consistent generation and editing results. For example, generation approaches usually fail to…

Computer Vision and Pattern Recognition · Computer Science 2023-04-18 Mingdeng Cao , Xintao Wang , Zhongang Qi , Ying Shan , Xiaohu Qie , Yinqiang Zheng

Object manipulation in images aims to not only edit the object's presentation but also gift objects with motion. Previous methods encountered challenges in concurrently handling static editing and dynamic generation, while also struggling…

Computer Vision and Pattern Recognition · Computer Science 2025-01-23 Ruisi Zhao , Zechuan Zhang , Zongxin Yang , Yi Yang

With the rapid advancement of intelligent transportation systems, text-driven image generation and editing techniques have demonstrated significant potential in providing rich, controllable visual scene data for applications such as traffic…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Feng Lv , Haoxuan Feng , Zilu Zhang , Chunlong Xia , Yanfeng Li

For embodied agents to infer representations of the underlying 3D physical world they inhabit, they should efficiently combine multisensory cues from numerous trials, e.g., by looking at and touching objects. Despite its importance,…

Machine Learning · Computer Science 2019-11-11 Jae Hyun Lim , Pedro O. Pinheiro , Negar Rostamzadeh , Christopher Pal , Sungjin Ahn

Creating large-scale interactive 3D environments is essential for the development of Robotics and Embodied AI research. Current methods, including manual design, procedural generation, diffusion-based scene generation, and large language…

Computer Vision and Pattern Recognition · Computer Science 2024-11-18 Yian Wang , Xiaowen Qiu , Jiageng Liu , Zhehuan Chen , Jiting Cai , Yufei Wang , Tsun-Hsuan Wang , Zhou Xian , Chuang Gan

As cutting-edge Text-to-Image (T2I) generation models already excel at producing remarkable single images, an even more challenging task, i.e., multi-turn interactive image generation begins to attract the attention of related research…

Computer Vision and Pattern Recognition · Computer Science 2025-06-02 Junhao Cheng , Xi Lu , Hanhui Li , Khun Loun Zai , Baiqiao Yin , Yuhao Cheng , Yiqiang Yan , Xiaodan Liang

In this paper, we investigate the problem of embodied multi-agent cooperation, where decentralized agents must cooperate given only egocentric views of the world. To effectively plan in this setting, in contrast to learning world dynamics…

Computer Vision and Pattern Recognition · Computer Science 2025-04-17 Hongxin Zhang , Zeyuan Wang , Qiushi Lyu , Zheyuan Zhang , Sunli Chen , Tianmin Shu , Behzad Dariush , Kwonjoon Lee , Yilun Du , Chuang Gan

In contrast to the traditional avatar creation pipeline which is a costly process, contemporary generative approaches directly learn the data distribution from photographs. While plenty of works extend unconditional generative models and…

Computer Vision and Pattern Recognition · Computer Science 2022-10-18 Junshu Tang , Bo Zhang , Binxin Yang , Ting Zhang , Dong Chen , Lizhuang Ma , Fang Wen

Humans excel at forecasting the future dynamics of a scene given just a single image. Video generation models that can mimic this ability are an essential component for intelligent systems. Recent approaches have improved temporal coherence…

Computer Vision and Pattern Recognition · Computer Science 2026-05-18 Melonie de Almeida , Daniela Ivanova , Tong Shi , John H. Williamson , Paul Henderson

Despite significant progress in diffusion-based image generation, subject-driven generation and instruction-based editing remain challenging. Existing methods typically treat them separately, struggling with limited high-quality data and…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Xueyun Tian , Wei Li , Bingbing Xu , Yige Yuan , Yuanzhuo Wang , Huawei Shen

We consider the task of generating realistic 3D shapes, which is useful for a variety of applications such as automatic scene generation and physical simulation. Compared to other 3D representations like voxels and point clouds, meshes are…

Graphics · Computer Science 2023-04-18 Zhen Liu , Yao Feng , Michael J. Black , Derek Nowrouzezahrai , Liam Paull , Weiyang Liu

Generating high-quality 3D assets from a given image is highly desirable in various applications such as AR/VR. Recent advances in single-image 3D generation explore feed-forward models that learn to infer the 3D model of an object without…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Yongwei Chen , Tengfei Wang , Tong Wu , Xingang Pan , Kui Jia , Ziwei Liu

Image generation today can produce somewhat realistic images from text prompts. However, if one asks the generator to synthesize a specific camera setting such as creating different fields of view using a 24mm lens versus a 70mm lens, the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Yu Yuan , Xijun Wang , Yichen Sheng , Prateek Chennuri , Xingguang Zhang , Stanley Chan

Generative models aim to learn the distribution of observed data by generating new instances. With the advent of neural networks, deep generative models, including variational autoencoders (VAEs), generative adversarial networks (GANs), and…

Computer Vision and Pattern Recognition · Computer Science 2023-08-29 Zifan Shi , Sida Peng , Yinghao Xu , Andreas Geiger , Yiyi Liao , Yujun Shen

Text-to-image generation has witnessed great progress, especially with the recent advancements in diffusion models. Since texts cannot provide detailed conditions like object appearance, reference images are usually leveraged for the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Zhiqi Huang , Huixin Xiong , Haoyu Wang , Longguang Wang , Zhiheng Li

LiDAR and camera are two modalities available for 3D semantic segmentation in autonomous driving. The popular LiDAR-only methods severely suffer from inferior segmentation on small and distant objects due to insufficient laser points, while…

Computer Vision and Pattern Recognition · Computer Science 2023-03-16 Jiale Li , Hang Dai , Hao Han , Yong Ding

With the rapid development of artificial intelligence (AI), digital humans have attracted more and more attention and are expected to achieve a wide range of applications in several industries. Then, most of the existing digital humans…

Multimedia · Computer Science 2023-11-01 Yingjie Zhou , Yaodong Chen , Kaiyue Bi , Lian Xiong , Hui Liu

The recent advances in text and image synthesis show a great promise for the future of generative models in creative fields. However, a less explored area is the one of 3D model generation, with a lot of potential applications to game…

Computer Vision and Pattern Recognition · Computer Science 2023-12-14 Antoine Schnepf , Flavian Vasile , Ugo Tanielian

Addressing the limitations of text as a source of accurate layout representation in text-conditional diffusion models, many works incorporate additional signals to condition certain attributes within a generated image. Although successful,…

Computer Vision and Pattern Recognition · Computer Science 2024-01-18 Jonghyun Lee , Hansam Cho , Youngjoon Yoo , Seoung Bum Kim , Yonghyun Jeong