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We introduce AnySplat, a feed forward network for novel view synthesis from uncalibrated image collections. In contrast to traditional neural rendering pipelines that demand known camera poses and per scene optimization, or recent feed…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Lihan Jiang , Yucheng Mao , Linning Xu , Tao Lu , Kerui Ren , Yichen Jin , Xudong Xu , Mulin Yu , Jiangmiao Pang , Feng Zhao , Dahua Lin , Bo Dai

Modeling and understanding the 3D world is crucial for various applications, from augmented reality to robotic navigation. Recent advancements based on 3D Gaussian Splatting have integrated semantic information from multi-view images into…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Xingrui Wang , Cuiling Lan , Hanxin Zhu , Zhibo Chen , Yan Lu

Sparse Multi-view Images can be Learned to predict explicit radiance fields via Generalizable Gaussian Splatting approaches, which can achieve wider application prospects in real-life when ground-truth camera parameters are not required as…

Computer Vision and Pattern Recognition · Computer Science 2024-11-28 Yanyan Li , Yixin Fang , Federico Tombari , Gim Hee Lee

3D Gaussian Splatting (3DGS) has emerged as a powerful technique for generating photorealistic renderings of a scene in real-time. However, the volumetric nature of 3DGS limits its ability to accurately capture surface geometry. To address…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Prajwal Gupta C. R. , Divyam Sheth , Jinjoo Ha , Mirela Ostrek , Justus Thies

3D Gaussian Splatting (GS) has emerged as a powerful representation for high-quality scene reconstruction, offering compelling rendering quality. However, the training process of GS often suffers from slow convergence due to inefficient…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Binxiao Huang , Zhengwu Liu , Ngai Wong

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

Reconstructing deformable endoscopic tissues is crucial for achieving robot-assisted surgery. However, 3D Gaussian Splatting-based approaches encounter challenges in achieving consistent tissue surface reconstruction, while existing…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Yangsen Chen , Hao Wang

Decompositional reconstruction of 3D scenes, with complete shapes and detailed texture of all objects within, is intriguing for downstream applications but remains challenging, particularly with sparse views as input. Recent approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Junfeng Ni , Yu Liu , Ruijie Lu , Zirui Zhou , Song-Chun Zhu , Yixin Chen , Siyuan Huang

This paper introduces SO(2)-Equivariant Gaussian Sculpting Networks (GSNs) as an approach for SO(2)-Equivariant 3D object reconstruction from single-view image observations. GSNs take a single observation as input to generate a Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Ruihan Xu , Anthony Opipari , Joshua Mah , Stanley Lewis , Haoran Zhang , Hanzhe Guo , Odest Chadwicke Jenkins

Sparse-view reconstruction models typically require precise camera poses, yet obtaining these parameters from sparse-view images remains challenging. We introduce FreeSplatter, a scalable feed-forward framework that generates high-quality…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Jiale Xu , Shenghua Gao , Ying Shan

Sparse-view 3D reconstruction is increasingly addressed with feed-forward splatting networks that predict explicit primitives directly from images. Yet most existing methods remain centered on Gaussian primitives and expose surfaces only…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Weijie Wang , Zimu Li , Jinchuan Shi , Zeyu Zhang , Botao Ye , Marc Pollefeys , Donny Y. Chen , Bohan Zhuang

3D Gaussian Splatting (3DGS) has demonstrated impressive novel view synthesis performance. While conventional methods require per-scene optimization, more recently several feed-forward methods have been proposed to generate pixel-aligned…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Shengjun Zhang , Xin Fei , Fangfu Liu , Haixu Song , Yueqi Duan

The increasing demand for augmented and virtual reality applications has highlighted the importance of crafting immersive 3D scenes from a simple single-view image. However, due to the partial priors provided by single-view input, existing…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Tianyi Gong , Boyan Li , Yifei Zhong , Fangxin Wang

Reconstructing 3D scenes using 3D Gaussian Splatting (3DGS) from sparse views is an ill-posed problem due to insufficient information, often resulting in noticeable artifacts. While recent approaches have sought to leverage generative…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Xingyilang Yin , Qi Zhang , Jiahao Chang , Ying Feng , Qingnan Fan , Xi Yang , Chi-Man Pun , Huaqi Zhang , Xiaodong Cun

3D Gaussian Splatting (3DGS) has recently unlocked real-time, high-fidelity novel view synthesis by representing scenes using explicit 3D primitives. However, traditional methods often require millions of Gaussians to capture complex…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Anh Thuan Tran , Jana Kosecka

3D Gaussian Splatting (3DGS) techniques have achieved satisfactory 3D scene representation. Despite their impressive performance, they confront challenges due to the limitation of structure-from-motion (SfM) methods on acquiring accurate…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Ao Gao , Luosong Guo , Tao Chen , Zhao Wang , Ying Tai , Jian Yang , Zhenyu Zhang

3D Gaussian splats have emerged as a revolutionary, effective, learned representation for static 3D scenes. In this work, we explore using 2D Gaussian splats as a new primitive for representing videos. We propose GSVC, an approach to…

Computer Vision and Pattern Recognition · Computer Science 2025-01-23 Longan Wang , Yuang Shi , Wei Tsang Ooi

Recent developments in 3D reconstruction and neural rendering have significantly propelled the capabilities of photo-realistic 3D scene rendering across various academic and industrial fields. The 3D Gaussian Splatting technique, alongside…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Zexu Huang , Min Xu , Stuart Perry

In this work, we propose a novel clothed human reconstruction method called GaussianBody, based on 3D Gaussian Splatting. Compared with the costly neural radiance based models, 3D Gaussian Splatting has recently demonstrated great…

Computer Vision and Pattern Recognition · Computer Science 2024-01-30 Mengtian Li , Shengxiang Yao , Zhifeng Xie , Keyu Chen

Given a single image of a target object, image-to-3D generation aims to reconstruct its texture and geometric shape. Recent methods often utilize intermediate media, such as multi-view images or videos, to bridge the gap between input image…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Jiacheng Wang , Zhedong Zheng , Wei Xu , Ping Liu