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Three-dimensional scene generation is crucial in computer vision, with applications spanning autonomous driving, gaming and the metaverse. Current methods either lack user control or rely on imprecise, non-intuitive conditions. In this…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Yuheng Liu , Xinke Li , Yuning Zhang , Lu Qi , Xin Li , Wenping Wang , Chongshou Li , Xueting Li , Ming-Hsuan Yang

As Artificial Intelligence Generated Content (AIGC) advances, a variety of methods have been developed to generate text, images, videos, and 3D objects from single or multimodal inputs, contributing efforts to emulate human-like cognitive…

Computer Vision and Pattern Recognition · Computer Science 2024-08-21 Yiying Yang , Fukun Yin , Jiayuan Fan , Xin Chen , Wanzhang Li , Gang Yu

We propose a diffusion-based approach for Text-to-Image (T2I) generation with interactive 3D layout control. Layout control has been widely studied to alleviate the shortcomings of T2I diffusion models in understanding objects' placement…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Abdelrahman Eldesokey , Peter Wonka

While current vision algorithms excel at many challenging tasks, it is unclear how well they understand the physical dynamics of real-world environments. Here we introduce Physion, a dataset and benchmark for rigorously evaluating the…

We focus on the foundational task of Scene Staging: given a reference scene image and a text condition specifying an actor category to be generated in the scene and its spatial relation to the scene, the goal is to synthesize an output…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Cong Xie , Che Wang , Yan Zhang , Ruiqi Yu , Han Zou , Zheng Pan , Zhenpeng Zhan

We introduce DiffPhysCam, a differentiable camera simulator designed to support robotics and embodied AI applications by enabling gradient-based optimization in visual perception pipelines. Generating synthetic images that closely mimic…

Graphics · Computer Science 2025-08-13 Bo-Hsun Chen , Nevindu M. Batagoda , Dan Negrut

Recent advancements in deep learning, computer vision, and embodied AI have given rise to synthetic causal reasoning video datasets. These datasets facilitate the development of AI algorithms that can reason about physical interactions…

Artificial Intelligence · Computer Science 2021-08-16 Jiafei Duan , Samson Yu Bai Jian , Cheston Tan

Realistic simulation of dynamic scenes requires accurately capturing diverse material properties and modeling complex object interactions grounded in physical principles. However, existing methods are constrained to basic material types…

Computer Vision and Pattern Recognition · Computer Science 2025-05-09 Zhuoman Liu , Weicai Ye , Yan Luximon , Pengfei Wan , Di Zhang

Achieving real-time physics-based animation that generalizes across diverse 3D shapes and discretizations remains a fundamental challenge. We introduce PhysSkin, a physics-informed framework that addresses this challenge. In the spirit of…

Indoor scene generation has attracted significant attention recently as it is crucial for applications of gaming, virtual reality, and interior design. Current indoor scene generation methods can produce reasonable room layouts but often…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Genghao Zhang , Yuxi Wang , Chuanchen Luo , Shibiao Xu , Zhaoxiang Zhang , Man Zhang , Junran Peng

Generating high-fidelity full-body human interactions with dynamic objects and static scenes remains a critical challenge in computer graphics and animation. Existing methods for human-object interaction often neglect scene context, leading…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Wei Yao , Yunlian Sun , Hongwen Zhang , Yebin Liu , Jinhui Tang

We present a method that simultaneously addresses the tasks of dynamic scene novel-view synthesis and six degree-of-freedom (6-DOF) tracking of all dense scene elements. We follow an analysis-by-synthesis framework, inspired by recent work…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Jonathon Luiten , Georgios Kopanas , Bastian Leibe , Deva Ramanan

Reconstructing physically stable 3D scenes from a single RGB image enables casual images to be converted into simulation-ready digital assets for applications such as immersive interaction and content creation. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Xiaoxuan Ma , Jiashun Wang , Nicolas Ugrinovic , Yehonathan Litman , Kris Kitani

Existing video generation models excel at producing photo-realistic videos from text or images, but often lack physical plausibility and 3D controllability. To overcome these limitations, we introduce PhysCtrl, a novel framework for…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Chen Wang , Chuhao Chen , Yiming Huang , Zhiyang Dou , Yuan Liu , Jiatao Gu , Lingjie Liu

The reconstruction of immersive and realistic 3D scenes holds significant practical importance in various fields of computer vision and computer graphics. Typically, immersive and realistic scenes should be free from obstructions by dynamic…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Zilong Huang , Jun He , Junyan Ye , Lihan Jiang , Weijia Li , Yiping Chen , Ting Han

Humans can naturally identify and mentally complete occluded objects in cluttered environments. However, imparting similar cognitive ability to robotics remains challenging even with advanced reconstruction techniques, which models scenes…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Zesong Yang , Bangbang Yang , Wenqi Dong , Chenxuan Cao , Liyuan Cui , Yuewen Ma , Zhaopeng Cui , Hujun Bao

Dynamic Scene Graphs (DSGs) provide a structured representation of hierarchical, interconnected environments, but current approaches struggle to capture stochastic dynamics, partial observability, and multi-agent activity. These aspects are…

Robotics · Computer Science 2025-10-13 Lars Ohnemus , Nils Hantke , Max Weißer , Kai Furmans

We propose a systematic learning-based approach to the generation of massive quantities of synthetic 3D scenes and arbitrary numbers of photorealistic 2D images thereof, with associated ground truth information, for the purposes of…

Computer Vision and Pattern Recognition · Computer Science 2018-06-21 Chenfanfu Jiang , Siyuan Qi , Yixin Zhu , Siyuan Huang , Jenny Lin , Lap-Fai Yu , Demetri Terzopoulos , Song-Chun Zhu

With the widespread use of virtual reality applications, 3D scene generation has become a new challenging research frontier. 3D scenes have highly complex structures and need to ensure that the output is dense, coherent, and contains all…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Xiaolu Hou , Mingcheng Li , Dingkang Yang , Jiawei Chen , Ziyun Qian , Xiao Zhao , Yue Jiang , Jinjie Wei , Qingyao Xu , Lihua Zhang

Recent breakthroughs in text-guided image generation have led to remarkable progress in the field of 3D synthesis from text. By optimizing neural radiance fields (NeRF) directly from text, recent methods are able to produce remarkable…

Computer Vision and Pattern Recognition · Computer Science 2023-03-24 Dana Cohen-Bar , Elad Richardson , Gal Metzer , Raja Giryes , Daniel Cohen-Or