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In the realm of computer vision and robotics, embodied agents are expected to explore their environment and carry out human instructions. This necessitates the ability to fully understand 3D scenes given their first-person observations and…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Tai Wang , Xiaohan Mao , Chenming Zhu , Runsen Xu , Ruiyuan Lyu , Peisen Li , Xiao Chen , Wenwei Zhang , Kai Chen , Tianfan Xue , Xihui Liu , Cewu Lu , Dahua Lin , Jiangmiao Pang

4D content generation aims to create dynamically evolving 3D content that responds to specific input objects such as images or 3D representations. Current approaches typically incorporate physical priors to animate 3D representations, but…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Jiajing Lin , Zhenzhong Wang , Dejun Xu , Shu Jiang , YunPeng Gong , Min Jiang

Synthesizing 3D human motion plays an important role in many graphics applications as well as understanding human activity. While many efforts have been made on generating realistic and natural human motion, most approaches neglect the…

Computer Vision and Pattern Recognition · Computer Science 2021-06-15 Jiashun Wang , Huazhe Xu , Jingwei Xu , Sifei Liu , Xiaolong Wang

Despite recent advances in text-conditioned 3D indoor scene generation, there remain gaps in the evaluation of these methods. Existing metrics often measure realism by comparing generated scenes to a set of ground-truth scenes, but they…

Graphics · Computer Science 2026-03-10 Hou In Ivan Tam , Hou In Derek Pun , Austin T. Wang , Angel X. Chang , Manolis Savva

Recent advances in 3D scene generation produce visually appealing output, but current representations hinder artists' workflows that require modifiable 3D textured mesh scenes for visual effects and game development. Despite significant…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Tobias Sautter , Jan-Niklas Dihlmann , Hendrik P. A. Lensch

Understanding the world in first-person view is fundamental in Augmented Reality (AR). This immersive perspective brings dramatic visual changes and unique challenges compared to third-person views. Synthetic data has empowered…

Computer Vision and Pattern Recognition · Computer Science 2024-04-12 Gen Li , Kaifeng Zhao , Siwei Zhang , Xiaozhong Lyu , Mihai Dusmanu , Yan Zhang , Marc Pollefeys , Siyu Tang

We study the problem of synthesizing immersive 3D indoor scenes from one or more images. Our aim is to generate high-resolution images and videos from novel viewpoints, including viewpoints that extrapolate far beyond the input images while…

Computer Vision and Pattern Recognition · Computer Science 2022-12-02 Jing Yu Koh , Harsh Agrawal , Dhruv Batra , Richard Tucker , Austin Waters , Honglak Lee , Yinfei Yang , Jason Baldridge , Peter Anderson

We introduce VividDream, a method for generating explorable 4D scenes with ambient dynamics from a single input image or text prompt. VividDream first expands an input image into a static 3D point cloud through iterative inpainting and…

Computer Vision and Pattern Recognition · Computer Science 2024-05-31 Yao-Chih Lee , Yi-Ting Chen , Andrew Wang , Ting-Hsuan Liao , Brandon Y. Feng , Jia-Bin Huang

Transforming static images into interactive experiences remains a challenging task in computer vision. Tackling this challenge holds the potential to elevate mobile user experiences, notably through interactive and AR/VR applications.…

Text-conditioned image generation has made significant progress in recent years with generative adversarial networks and more recently, diffusion models. While diffusion models conditioned on text prompts have produced impressive and…

Computer Vision and Pattern Recognition · Computer Science 2023-05-01 Azade Farshad , Yousef Yeganeh , Yu Chi , Chengzhi Shen , Björn Ommer , Nassir Navab

Constructing compact and informative 3D scene representations is essential for effective embodied exploration and reasoning, especially in complex environments over extended periods. Existing representations, such as object-centric 3D scene…

Computer Vision and Pattern Recognition · Computer Science 2025-04-07 Yuncong Yang , Han Yang , Jiachen Zhou , Peihao Chen , Hongxin Zhang , Yilun Du , Chuang Gan

As pretrained text-to-image diffusion models become increasingly powerful, recent efforts have been made to distill knowledge from these text-to-image pretrained models for optimizing a text-guided 3D model. Most of the existing methods…

Computer Vision and Pattern Recognition · Computer Science 2024-06-12 Gege Gao , Weiyang Liu , Anpei Chen , Andreas Geiger , Bernhard Schölkopf

General physical scene understanding requires more than simply localizing and recognizing objects -- it requires knowledge that objects can have different latent properties (e.g., mass or elasticity), and that those properties affect the…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Hsiao-Yu Tung , Mingyu Ding , Zhenfang Chen , Daniel Bear , Chuang Gan , Joshua B. Tenenbaum , Daniel LK Yamins , Judith E Fan , Kevin A. Smith

We introduce a novel method for dynamic free-view synthesis of an ambient scenes from a monocular capture bringing a immersive quality to the viewing experience. Our method builds upon the recent advancements in 3D Gaussian Splatting (3DGS)…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Meng-Li Shih , Jia-Bin Huang , Changil Kim , Rajvi Shah , Johannes Kopf , Chen Gao

The creation of 3D scenes has traditionally been both labor-intensive and costly, requiring designers to meticulously configure 3D assets and environments. Recent advancements in generative AI, including text-to-3D and image-to-3D methods,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Ziyang Yan , Yihua Shao , Minwen Liao , Siyu Chen , Nan Wang , Muyuan Lin , Jenq-Neng Hwang , Hao Zhao , Fabio Remondino , Lei Li

Generating high-fidelity, physically interactive 3D simulated tabletop scenes is essential for embodied AI -- especially for robotic manipulation policy learning and data synthesis. However, current text- or image-driven 3D scene generation…

Computer Vision and Pattern Recognition · Computer Science 2025-12-08 Ziqian Wang , Yonghao He , Licheng Yang , Wei Zou , Hongxuan Ma , Liu Liu , Wei Sui , Yuxin Guo , Hu Su

3D-aware GANs aim to synthesize realistic 3D scenes such that they can be rendered in arbitrary perspectives to produce images. Although previous methods produce realistic images, they suffer from unstable training or degenerate solutions…

Computer Vision and Pattern Recognition · Computer Science 2023-11-13 Minjung Shin , Yunji Seo , Jeongmin Bae , Young Sun Choi , Hyunsu Kim , Hyeran Byun , Youngjung Uh

The creation of complex 3D scenes tailored to user specifications has been a tedious and challenging task with traditional 3D modeling tools. Although some pioneering methods have achieved automatic text-to-3D generation, they are generally…

Computer Vision and Pattern Recognition · Computer Science 2025-05-09 Xiuyu Yang , Yunze Man , Jun-Kun Chen , Yu-Xiong Wang

Generating realistic 3D scenes is an area of growing interest in computer vision and robotics. However, creating high-quality, diverse synthetic 3D content often requires expert intervention, making it costly and complex. Recently, efforts…

Computer Vision and Pattern Recognition · Computer Science 2024-12-11 Siyi Hu , Diego Martin Arroyo , Stephanie Debats , Fabian Manhardt , Luca Carlone , Federico Tombari

We present a Polyhedral Scene Generator system which creates a random scene based on a few user parameters, renders the scene from random view points and creates a dataset containing the renderings and corresponding annotation files. We…

Computer Vision and Pattern Recognition · Computer Science 2018-03-28 Markus D. Solbach , Stephen Voland , Jeff Edmonds , John K. Tsotsos