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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

Volumetric scene reconstruction from a single image is crucial for a broad range of applications like autonomous driving and robotics. Recent volumetric reconstruction methods achieve impressive results, but generally require expensive 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Philipp Wulff , Felix Wimbauer , Dominik Muhle , Daniel Cremers

We introduce PAT3D, the first physics-augmented text-to-3D scene generation framework that integrates vision-language models with physics-based simulation to produce physically plausible, simulation-ready, and intersection-free 3D scenes.…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Guying Lin , Kemeng Huang , Michael Liu , Ruihan Gao , Hanke Chen , Lyuhao Chen , Beijia Lu , Taku Komura , Yuan Liu , Jun-Yan Zhu , Minchen Li

As a promising 3D generation technique, multiview diffusion (MVD) has received a lot of attention due to its advantages in terms of generalizability, quality, and efficiency. By finetuning pretrained large image diffusion models with 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 Xin-Yang Zheng , Hao Pan , Yu-Xiao Guo , Xin Tong , Yang Liu

Creating flexible 3D scenes from a single image is vital when direct 3D data acquisition is costly or impractical. We introduce NavCrafter, a novel framework that explores 3D scenes from a single image by synthesizing novel-view video…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Hongbo Duan , Peiyu Zhuang , Yi Liu , Zhengyang Zhang , Yuxin Zhang , Pengting Luo , Fangming Liu , Xueqian Wang

We propose a novel approach for 3D video synthesis that is able to represent multi-view video recordings of a dynamic real-world scene in a compact, yet expressive representation that enables high-quality view synthesis and motion…

Computer Vision and Pattern Recognition · Computer Science 2022-05-04 Tianye Li , Mira Slavcheva , Michael Zollhoefer , Simon Green , Christoph Lassner , Changil Kim , Tanner Schmidt , Steven Lovegrove , Michael Goesele , Richard Newcombe , Zhaoyang Lv

Explorable 3D world generation from a single image or text prompt forms a cornerstone of spatial intelligence. Recent works utilize video model to achieve wide-scope and generalizable 3D world generation. However, existing approaches often…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Zhongqi Yang , Wenhang Ge , Yuqi Li , Jiaqi Chen , Haoyuan Li , Mengyin An , Fei Kang , Hua Xue , Baixin Xu , Yuyang Yin , Eric Li , Yang Liu , Yikai Wang , Hao-Xiang Guo , Yahui Zhou

In this paper, we propose VistaDream a novel framework to reconstruct a 3D scene from a single-view image. Recent diffusion models enable generating high-quality novel-view images from a single-view input image. Most existing methods only…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Haiping Wang , Yuan Liu , Ziwei Liu , Wenping Wang , Zhen Dong , Bisheng Yang

Diffusion models have recently become the de-facto approach for generative modeling in the 2D domain. However, extending diffusion models to 3D is challenging due to the difficulties in acquiring 3D ground truth data for training. On the…

Computer Vision and Pattern Recognition · Computer Science 2023-10-27 Jiatao Gu , Qingzhe Gao , Shuangfei Zhai , Baoquan Chen , Lingjie Liu , Josh Susskind

In this paper, we introduce \textbf{DimensionX}, a framework designed to generate photorealistic 3D and 4D scenes from just a single image with video diffusion. Our approach begins with the insight that both the spatial structure of a 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Wenqiang Sun , Shuo Chen , Fangfu Liu , Zilong Chen , Yueqi Duan , Jun Zhang , Yikai Wang

We present a novel diffusion-based approach for coherent 3D scene reconstruction from a single RGB image. Our method utilizes an image-conditioned 3D scene diffusion model to simultaneously denoise the 3D poses and geometries of all objects…

Computer Vision and Pattern Recognition · Computer Science 2024-12-16 Manuel Dahnert , Angela Dai , Norman Müller , Matthias Nießner

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

The generation of 3D scenes from user-specified conditions offers a promising avenue for alleviating the production burden in 3D applications. Previous studies required significant effort to realize the desired scene, owing to limited…

Computer Vision and Pattern Recognition · Computer Science 2024-11-28 Takayuki Hara , Tatsuya Harada

The growing demand for Embodied AI and VR applications has highlighted the need for synthesizing high-quality 3D indoor scenes from sparse inputs. However, existing approaches struggle to infer massive amounts of missing geometry in large…

Computer Vision and Pattern Recognition · Computer Science 2026-04-15 Dehui Wang , Congsheng Xu , Rong Wei , Yue Shi , Shoufa Chen , Dingxiang Luo , Tianshuo Yang , Xiaokang Yang , Wei Sui , Yusen Qin , Rui Tang , Yao Mu

Recent advances in 4D generation mainly focus on generating 4D content by distilling pre-trained text or single-view image-conditioned models. It is inconvenient for them to take advantage of various off-the-shelf 3D assets with multi-view…

Computer Vision and Pattern Recognition · Computer Science 2024-09-10 Yanqin Jiang , Chaohui Yu , Chenjie Cao , Fan Wang , Weiming Hu , Jin Gao

Diffusion models (DMs) excel in photo-realistic image synthesis, but their adaptation to LiDAR scene generation poses a substantial hurdle. This is primarily because DMs operating in the point space struggle to preserve the curve-like…

Computer Vision and Pattern Recognition · Computer Science 2024-04-22 Haoxi Ran , Vitor Guizilini , Yue Wang

In this paper, we learn a diffusion model to generate 3D data on a scene-scale. Specifically, our model crafts a 3D scene consisting of multiple objects, while recent diffusion research has focused on a single object. To realize our goal,…

Computer Vision and Pattern Recognition · Computer Science 2023-01-03 Jumin Lee , Woobin Im , Sebin Lee , Sung-Eui Yoon

Generating novel views of a natural scene, e.g., every-day scenes both indoors and outdoors, from a single view is an under-explored problem, even though it is an organic extension to the object-centric novel view synthesis. Existing…

Computer Vision and Pattern Recognition · Computer Science 2025-11-13 Wonbong Jang , Jonathan Tremblay , Lourdes Agapito

In this paper, we introduce \textit{DecoRec}, a novel system designed to elevate single-view 2D images to a decomposed 3D scene mesh. Current methods for single-view scene reconstruction typically rely on object retrieval or the regression…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Yuhan Ping , Yuan Liu , Xiaoxiao Long , Peng Wang , Junhui Hou , Jianyi Zheng , Jia Pan , Xin Li , Cheng Lin

Prior approaches injecting camera control into diffusion models have focused on specific subsets of 4D consistency tasks: novel view synthesis, text-to-video with camera control, image-to-video, amongst others. Therefore, these fragmented…

Computer Vision and Pattern Recognition · Computer Science 2026-01-26 Xiang Fan , Sharath Girish , Vivek Ramanujan , Chaoyang Wang , Ashkan Mirzaei , Petr Sushko , Aliaksandr Siarohin , Sergey Tulyakov , Ranjay Krishna