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Generating explorable 3D scenes from a single image is a highly challenging problem in 3D vision. Existing methods struggle to support free exploration, often producing severe geometric distortions and noisy artifacts when the viewpoint…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Pengfei Wang , Liyi Chen , Zhiyuan Ma , Yanjun Guo , Guowen Zhang , Lei Zhang

Realistic video simulation has shown significant potential across diverse applications, from virtual reality to film production. This is particularly true for scenarios where capturing videos in real-world settings is either impractical or…

Computer Vision and Pattern Recognition · Computer Science 2024-02-01 Chen Bai , Zeman Shao , Guoxiang Zhang , Di Liang , Jie Yang , Zhuorui Zhang , Yujian Guo , Chengzhang Zhong , Yiqiao Qiu , Zhendong Wang , Yichen Guan , Xiaoyin Zheng , Tao Wang , Cheng Lu

Existing methods for reconstructing objects and humans from a monocular image suffer from severe mesh collisions and performance limitations for interacting occluding objects. This paper introduces a method to obtain a globally consistent…

Computer Vision and Pattern Recognition · Computer Science 2024-08-16 Sarthak Batra , Partha P. Chakrabarti , Simon Hadfield , Armin Mustafa

The demand for efficient 3D model generation techniques has grown exponentially, as manual creation of 3D models is time-consuming and requires specialized expertise. While generative models have shown potential in creating 3D textured…

Computer Vision and Pattern Recognition · Computer Science 2023-07-28 Fanghua Yu , Xintao Wang , Zheyuan Li , Yan-Pei Cao , Ying Shan , Chao Dong

Understanding, navigating, and exploring the 3D physical real world has long been a central challenge in the development of artificial intelligence. In this work, we take a step toward this goal by introducing GenEx, a system capable of…

Computer Vision and Pattern Recognition · Computer Science 2025-01-22 Taiming Lu , Tianmin Shu , Junfei Xiao , Luoxin Ye , Jiahao Wang , Cheng Peng , Chen Wei , Daniel Khashabi , Rama Chellappa , Alan Yuille , Jieneng Chen

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

The rise of generalist robotic policies has created an exponential demand for large-scale training data. However, on-robot data collection is labor-intensive and often limited to specific environments. In contrast, open-world images capture…

Given a single image of a general object such as a chair, could we also restore its articulated 3D shape similar to human modeling, so as to animate its plausible articulations and diverse motions? This is an interesting new question that…

Computer Vision and Pattern Recognition · Computer Science 2022-07-07 Ji Yang , Xinxin Zuo , Sen Wang , Zhenbo Yu , Xingyu Li , Bingbing Ni , Minglun Gong , Li Cheng

How can one efficiently generate high-quality, wide-scope 3D scenes from arbitrary single images? Existing methods suffer several drawbacks, such as requiring multi-view data, time-consuming per-scene optimization, distorted geometry in…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Hanwen Liang , Junli Cao , Vidit Goel , Guocheng Qian , Sergei Korolev , Demetri Terzopoulos , Konstantinos N. Plataniotis , Sergey Tulyakov , Jian Ren

3D Content Generation is at the heart of many computer graphics applications, including video gaming, film-making, virtual and augmented reality, etc. This paper proposes a novel deep-learning based approach for automatically generating…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Yongzhi Xu , Yonhon Ng , Yifu Wang , Inkyu Sa , Yunfei Duan , Zhenhong Sun , Yang Li , Pan Ji , Hongdong Li

Recent progress in video generation has led to substantial improvements in visual fidelity, yet ensuring physically consistent motion remains a fundamental challenge. Intuitively, this limitation can be attributed to the fact that…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Cong Wang , Hanxin Zhu , Xiao Tang , Jiayi Luo , Xin Jin , Long Chen , Zhibo Chen

Marker-less 3D human motion capture from a single colour camera has seen significant progress. However, it is a very challenging and severely ill-posed problem. In consequence, even the most accurate state-of-the-art approaches have…

Computer Vision and Pattern Recognition · Computer Science 2020-12-10 Soshi Shimada , Vladislav Golyanik , Weipeng Xu , Christian Theobalt

Controllable generative models for images and videos have seen significant success, yet 3D scene generation, especially in unbounded scenarios like autonomous driving, remains underdeveloped. Existing methods lack flexible controllability…

Computer Vision and Pattern Recognition · Computer Science 2025-07-28 Ruiyuan Gao , Kai Chen , Zhihao Li , Lanqing Hong , Zhenguo Li , Qiang Xu

We address the task of generating physically accurate and visually faithful 4D Human-Object Interaction (HOI). Given a static 3D human and target object represented as 3D Gaussian Splats (3DGS), our goal is to synthesize dynamic scenes…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Omer Benishu , Gal Fiebelman , Sagie Benaim

We present a single-image 3D face synthesis technique that can handle challenging facial expressions while recovering fine geometric details. Our technique employs expression analysis for proxy face geometry generation and combines…

Computer Vision and Pattern Recognition · Computer Science 2019-12-04 Anpei Chen , Zhang Chen , Guli Zhang , Ziheng Zhang , Kenny Mitchell , Jingyi Yu

Given a 3D mesh, we aim to synthesize 3D textures that correspond to arbitrary textual descriptions. Current methods for generating and assembling textures from sampled views often result in prominent seams or excessive smoothing. To tackle…

Computer Vision and Pattern Recognition · Computer Science 2024-08-05 Dong Huo , Zixin Guo , Xinxin Zuo , Zhihao Shi , Juwei Lu , Peng Dai , Songcen Xu , Li Cheng , Yee-Hong Yang

View-predictive generative models provide strong priors for lifting object-centric images and videos into 3D and 4D through rendering and score distillation objectives. A question then remains: what about lifting complete multi-object…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Wen-Hsuan Chu , Lei Ke , Katerina Fragkiadaki

Automatically generating a complete 3D scene from a text description, a reference image, or both has significant applications in fields like virtual reality and gaming. However, current methods often generate low-quality textures and…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Zhexiao Xiong , Zhang Chen , Zhong Li , Yi Xu , Nathan Jacobs

Recent progress in image and video synthesis has inspired their use in advancing 3D scene generation. However, we observe that text-to-image and -video approaches struggle to maintain scene- and object-level consistency beyond a limited…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Manuel-Andreas Schneider , Angela Dai

Creating realistic 3D animation remains a time-consuming and expertise-dependent process, requiring manual rigging, keyframing, and fine-tuning of complex motions. Meanwhile, video diffusion models have recently demonstrated remarkable…

Graphics · Computer Science 2025-12-17 Tianyi Xie , Yunuo Chen , Yaowei Guo , Yin Yang , Bolei Zhou , Demetri Terzopoulos , Ying Jiang , Chenfanfu Jiang