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Open-vocabulary panoptic reconstruction is a challenging task for simultaneous scene reconstruction and understanding. Recently, methods have been proposed for 3D scene understanding based on Gaussian splatting. However, these methods are…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Yuxuan Xie , Xuan Yu , Changjian Jiang , Sitong Mao , Shunbo Zhou , Rui Fan , Rong Xiong , Yue Wang

We introduce GeoGS3D, a novel two-stage framework for reconstructing detailed 3D objects from single-view images. Inspired by the success of pre-trained 2D diffusion models, our method incorporates an orthogonal plane decomposition…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Qijun Feng , Zhen Xing , Zuxuan Wu , Yu-Gang Jiang

360$^\circ$ panoramas are extensively utilized as environmental light sources in computer graphics. However, capturing a 360$^\circ$ $\times$ 180$^\circ$ panorama poses challenges due to the necessity of specialized and costly equipment,…

Computer Vision and Pattern Recognition · Computer Science 2023-08-29 Jionghao Wang , Ziyu Chen , Jun Ling , Rong Xie , Li Song

We propose GS-LRM, a scalable large reconstruction model that can predict high-quality 3D Gaussian primitives from 2-4 posed sparse images in 0.23 seconds on single A100 GPU. Our model features a very simple transformer-based architecture;…

Computer Vision and Pattern Recognition · Computer Science 2024-05-01 Kai Zhang , Sai Bi , Hao Tan , Yuanbo Xiangli , Nanxuan Zhao , Kalyan Sunkavalli , Zexiang Xu

Panoramic video generation enables immersive 360{\deg} content creation, valuable in applications that demand scene-consistent world exploration. However, existing panoramic video generation models struggle to leverage pre-trained…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Yifei Xia , Shuchen Weng , Siqi Yang , Jingqi Liu , Chengxuan Zhu , Minggui Teng , Zijian Jia , Han Jiang , Boxin Shi

Semantic-aware 3D reconstruction from sparse, unposed images remains challenging for feed-forward 3D Gaussian Splatting (3DGS). Existing methods often predict an over-complete set of Gaussian primitives under sparse-view supervision,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Guibiao Liao , Qian Ren , Kaimin Liao , Hua Wang , Zhi Chen , Luchao Wang , Yaohua Tang

We present a fast and efficient volumetric capture and reconstruction system that processes either RGB-D or RGB-only input to generate 3D representations in the form of point clouds and Gaussian splats. For Gaussian splat reconstructions,…

Graphics · Computer Science 2025-12-19 Athanasios Charisoudis , Simone Croci , Lam Kit Yung , Pascal Frossard , Aljosa Smolic

3D Gaussian Splat (3DGS) enables high-fidelity, real-time novel view synthesis by representing scenes with large sets of anisotropic primitives, but often requires millions of Splats, incurring significant storage and transmission costs.…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Butian Xiong , Rong Liu , Tiantian Zhou , Meida Chen , Zhiwen Fan , Andrew Feng

We present a unique system for large-scale, multi-performer, high resolution 4D volumetric capture providing realistic free-viewpoint video up to and including 4K resolution facial closeups. To achieve this, we employ a novel volumetric…

We introduce GRM, a large-scale reconstructor capable of recovering a 3D asset from sparse-view images in around 0.1s. GRM is a feed-forward transformer-based model that efficiently incorporates multi-view information to translate the input…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 Yinghao Xu , Zifan Shi , Wang Yifan , Hansheng Chen , Ceyuan Yang , Sida Peng , Yujun Shen , Gordon Wetzstein

We aim to address sparse-view reconstruction of a 3D scene by leveraging priors from large-scale vision models. While recent advancements such as 3D Gaussian Splatting (3DGS) have demonstrated remarkable successes in 3D reconstruction,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Hanyang Yu , Xiaoxiao Long , Ping Tan

Representing and rendering dynamic scenes has been an important but challenging task. Especially, to accurately model complex motions, high efficiency is usually hard to guarantee. To achieve real-time dynamic scene rendering while also…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Guanjun Wu , Taoran Yi , Jiemin Fang , Lingxi Xie , Xiaopeng Zhang , Wei Wei , Wenyu Liu , Qi Tian , Xinggang Wang

3D scene generation is in high demand across various domains, including virtual reality, gaming, and the film industry. Owing to the powerful generative capabilities of text-to-image diffusion models that provide reliable priors, the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Haiyang Zhou , Xinhua Cheng , Wangbo Yu , Yonghong Tian , Li Yuan

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

The visual world we sense, interpret and interact everyday is a complex composition of interleaved physical entities. Therefore, it is a very challenging task to generate vivid scenes of similar complexity using computers. In this work, we…

Computer Vision and Pattern Recognition · Computer Science 2019-02-05 Mehmet Ozgur Turkoglu , William Thong , Luuk Spreeuwers , Berkay Kicanaoglu

Embodied AI (EAI) research requires high-quality, diverse 3D scenes to effectively support skill acquisition, sim-to-real transfer, and generalization. Achieving these quality standards, however, necessitates the precise replication of…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Huangyue Yu , Baoxiong Jia , Yixin Chen , Yandan Yang , Puhao Li , Rongpeng Su , Jiaxin Li , Qing Li , Wei Liang , Song-Chun Zhu , Tengyu Liu , Siyuan Huang

We present a generalizable feed-forward Gaussian splatting framework for human 3D reconstruction and real-time animation that operates directly on multi-view RGB images and their associated SMPL-X poses. Unlike prior methods that rely on…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Devdoot Chatterjee , Zakaria Laskar , C. V. Jawahar

Panoramic video generation aims to synthesize 360-degree immersive videos, holding significant importance in the fields of VR, world models, and spatial intelligence. Existing works fail to synthesize high-quality panoramic videos due to…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Zixun Fang , Kai Zhu , Zhiheng Liu , Yu Liu , Wei Zhai , Yang Cao , Zheng-Jun Zha

3D Gaussian Splatting (3DGS) has recently enabled real-time rendering of unbounded 3D scenes for novel view synthesis. However, this technique requires dense training views to accurately reconstruct 3D geometry. A limited number of input…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Haolin Xiong , Sairisheek Muttukuru , Rishi Upadhyay , Pradyumna Chari , Achuta Kadambi

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