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We present DreamWaltz, a novel framework for generating and animating complex 3D avatars given text guidance and parametric human body prior. While recent methods have shown encouraging results for text-to-3D generation of common objects,…

Computer Vision and Pattern Recognition · Computer Science 2023-11-07 Yukun Huang , Jianan Wang , Ailing Zeng , He Cao , Xianbiao Qi , Yukai Shi , Zheng-Jun Zha , Lei Zhang

To achieve realistic immersion in landscape images, fluids such as water and clouds need to move within the image while revealing new scenes from various camera perspectives. Recently, a field called dynamic scene video has emerged, which…

Computer Vision and Pattern Recognition · Computer Science 2025-04-09 In-Hwan Jin , Haesoo Choo , Seong-Hun Jeong , Heemoon Park , Junghwan Kim , Oh-joon Kwon , Kyeongbo Kong

In this paper, we propose Scene Splatter, a momentum-based paradigm for video diffusion to generate generic scenes from single image. Existing methods, which employ video generation models to synthesize novel views, suffer from limited…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Shengjun Zhang , Jinzhao Li , Xin Fei , Hao Liu , Yueqi Duan

Large-scale video generative models can synthesize diverse and realistic visual content for dynamic world creation, but they often lack element-wise controllability, hindering their use in editing scenes and training embodied AI agents. We…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Sicheng Mo , Ziyang Leng , Leon Liu , Weizhen Wang , Honglin He , Bolei Zhou

Generating immersive 3D scenes from texts is a core task in computer vision, crucial for applications in virtual reality and game development. Despite the promise of leveraging 2D diffusion priors, existing methods suffer from spatial…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Jisheng Chu , Wenrui Li , Rui Zhao , Wangmeng Zuo , Shifeng Chen , Xiaopeng Fan

The synthesis of immersive 3D scenes from text is rapidly maturing, driven by novel video generative models and feed-forward 3D reconstruction, with vast potential in AR/VR and world modeling. While panoramic images have proven effective…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Felix Wimbauer , Fabian Manhardt , Michael Oechsle , Nikolai Kalischek , Christian Rupprecht , Daniel Cremers , Federico Tombari

We introduce a method to generate 3D scenes that are disentangled into their component objects. This disentanglement is unsupervised, relying only on the knowledge of a large pretrained text-to-image model. Our key insight is that objects…

Computer Vision and Pattern Recognition · Computer Science 2024-02-28 Dave Epstein , Ben Poole , Ben Mildenhall , Alexei A. Efros , Aleksander Holynski

Humans possess a remarkable ability to mentally explore and replay 3D environments they have previously experienced. Inspired by this mental process, we present EvoWorld: a world model that bridges panoramic video generation with evolving…

Computer Vision and Pattern Recognition · Computer Science 2025-10-02 Jiahao Wang , Luoxin Ye , TaiMing Lu , Junfei Xiao , Jiahan Zhang , Yuxiang Guo , Xijun Liu , Rama Chellappa , Cheng Peng , Alan Yuille , Jieneng Chen

3D indoor scenes are widely used in computer graphics, with applications ranging from interior design to gaming to virtual and augmented reality. They also contain rich information, including room layout, as well as furniture type,…

Graphics · Computer Science 2023-02-22 Lin Gao , Jia-Mu Sun , Kaichun Mo , Yu-Kun Lai , Leonidas J. Guibas , Jie Yang

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

Synthesizing consistent and photorealistic 3D scenes is an open problem in computer vision. Video diffusion models generate impressive videos but cannot directly synthesize 3D representations, i.e., lack 3D consistency in the generated…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Katja Schwarz , Norman Mueller , Peter Kontschieder

This work introduces a new task of instance-incremental scene graph generation: Given a scene of the point cloud, representing it as a graph and automatically increasing novel instances. A graph denoting the object layout of the scene is…

Computer Vision and Pattern Recognition · Computer Science 2023-08-29 Chao Qi , Jianqin Yin , Jinghang Xu , Pengxiang Ding

We present InfiniCube, a scalable method for generating unbounded dynamic 3D driving scenes with high fidelity and controllability. Previous methods for scene generation either suffer from limited scales or lack geometric and appearance…

Computer Vision and Pattern Recognition · Computer Science 2025-06-27 Yifan Lu , Xuanchi Ren , Jiawei Yang , Tianchang Shen , Zhangjie Wu , Jun Gao , Yue Wang , Siheng Chen , Mike Chen , Sanja Fidler , Jiahui Huang

We introduce Diff4Splat, a feed-forward method that synthesizes controllable and explicit 4D scenes from a single image. Our approach unifies the generative priors of video diffusion models with geometry and motion constraints learned from…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Panwang Pan , Chenguo Lin , Jingjing Zhao , Chenxin Li , Yuchen Lin , Haopeng Li , Honglei Yan , Kairun Wen , Yunlong Lin , Yixuan Yuan , Yadong Mu

We address the problem of generating videos from unposed internet photos. A handful of input images serve as keyframes, and our model interpolates between them to simulate a path moving between the cameras. Given random images, a model's…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Gene Chou , Kai Zhang , Sai Bi , Hao Tan , Zexiang Xu , Fujun Luan , Bharath Hariharan , Noah Snavely

Recent single-view 3D generative methods have made significant advancements by leveraging knowledge distilled from extensive 3D object datasets. However, challenges persist in the synthesis of 3D scenes from a single view, primarily due to…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Guo Pu , Yiming Zhao , Zhouhui Lian

We embark on the age-old quest: unveiling the hidden dimensions of objects from mere glimpses of their visible parts. To address this, we present Vista3D, a framework that realizes swift and consistent 3D generation within a mere 5 minutes.…

Computer Vision and Pattern Recognition · Computer Science 2024-09-19 Qiuhong Shen , Xingyi Yang , Michael Bi Mi , Xinchao Wang

Recent advances in diffusion models have revolutionized 2D and 3D content creation, yet generating photorealistic dynamic 4D scenes remains a significant challenge. Existing dynamic 4D generation methods typically rely on distilling…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Vinayak Gupta , Yunze Man , Yu-Xiong Wang

City scene generation has gained significant attention in autonomous driving, smart city development, and traffic simulation. It helps enhance infrastructure planning and monitoring solutions. Existing methods have employed a two-stage…

Computer Vision and Pattern Recognition · Computer Science 2024-06-10 Jie Deng , Wenhao Chai , Junsheng Huang , Zhonghan Zhao , Qixuan Huang , Mingyan Gao , Jianshu Guo , Shengyu Hao , Wenhao Hu , Jenq-Neng Hwang , Xi Li , Gaoang Wang

Recovering 4D world from monocular video is a crucial yet challenging task. Conventional methods usually rely on the assumptions of multi-view videos, known camera parameters, or static scenes. In this paper, we relax all these constraints…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Shizun Wang , Xingyi Yang , Qiuhong Shen , Zhenxiang Jiang , Xinchao Wang