English
Related papers

Related papers: Less Gaussians, Texture More: 4K Feed-Forward Text…

200 papers

With the advent of portable 360{\deg} cameras, panorama has gained significant attention in applications like virtual reality (VR), virtual tours, robotics, and autonomous driving. As a result, wide-baseline panorama view synthesis has…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Cheng Zhang , Haofei Xu , Qianyi Wu , Camilo Cruz Gambardella , Dinh Phung , Jianfei Cai

Despite advances in physics-based 3D motion synthesis, current methods face key limitations: reliance on pre-reconstructed 3D Gaussian Splatting (3DGS) built from dense multi-view images with time-consuming per-scene optimization; physics…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Chunji Lv , Zequn Chen , Donglin Di , Weinan Zhang , Hao Li , Wei Chen , Yinjie Lei , Changsheng Li

We introduce GaussianZoom, a generative zoom-in 3D reconstruction system with an iterative progressive framework that combines geometry-consistent scene modeling and multi-scale semantic reasoning to enable high-fidelity extreme zoom-in…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Jiale Shi , Jiarui Hu , Zesong Yang , Kaixuan Luan , Hujun Bao , Zhaopeng Cui

Recent advances in feed-forward 3D Gaussian Splatting have led to rapid improvements in efficient scene reconstruction from sparse views. However, most existing approaches construct Gaussian primitives directly aligned with the pixels in…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Yiming Wang , Lucy Chai , Xuan Luo , Michael Niemeyer , Manuel Lagunas , Stephen Lombardi , Siyu Tang , Tiancheng Sun

Gaussian splatting techniques have shown promising results in novel view synthesis, achieving high fidelity and efficiency. However, their high reconstruction quality comes at the cost of requiring a large number of primitives. We identify…

Graphics · Computer Science 2025-07-29 Xin Zhang , Anpei Chen , Jincheng Xiong , Pinxuan Dai , Yujun Shen , Weiwei Xu

Novel-view synthesis and 3D reconstruction from sparse posed images are central to robotics and AR/VR. Yet, feed-forward 3D Gaussian reconstruction fails under lowlight due to noise, color shifts, and unreliable correspondence. We propose…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Fuzhen Jiang , Zengtian Xie , Zhuoran Li

3D scene reconstruction is fundamental for spatial intelligence applications such as AR, robotics, and digital twins. Traditional multi-view stereo struggles with sparse viewpoints or low-texture regions, while neural rendering approaches,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Jiaqi Yao , Zhongmiao Yan , Jingyi Xu , Songpengcheng Xia , Yan Xiang , Ling Pei

Recently, the integration of the efficient feed-forward scheme into 3D Gaussian Splatting (3DGS) has been actively explored. However, most existing methods focus on sparse view reconstruction of small regions and cannot produce eligible…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Yunsong Wang , Tianxin Huang , Hanlin Chen , Gim Hee Lee

Feed-forward 3D Gaussian Splatting (3DGS) models enable real-time scene generation but are hindered by suboptimal pixel-aligned primitive placement, which relies on a dense, rigid grid that limits both quality and efficiency. We introduce a…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Arthur Moreau , Richard Shaw , Michal Nazarczuk , Jisu Shin , Thomas Tanay , Zhensong Zhang , Songcen Xu , Eduardo Pérez-Pellitero

Feed-forward 3D modeling has emerged as a promising approach for rapid and high-quality 3D reconstruction. In particular, directly generating explicit 3D representations, such as 3D Gaussian splatting, has attracted significant attention…

Computer Vision and Pattern Recognition · Computer Science 2025-10-20 Gyeongjin Kang , Seungtae Nam , Seungkwon Yang , Xiangyu Sun , Sameh Khamis , Abdelrahman Mohamed , Eunbyung Park

A major breakthrough in 3D reconstruction is the feedforward paradigm to generate pixel-wise 3D points or Gaussian primitives from sparse, unposed images. To further incorporate semantics while avoiding the significant memory and storage…

Computer Vision and Pattern Recognition · Computer Science 2025-10-13 Yu Sheng , Jiajun Deng , Xinran Zhang , Yu Zhang , Bei Hua , Yanyong Zhang , Jianmin Ji

We present billboard Splatting (BBSplat) - a novel approach for novel view synthesis based on textured geometric primitives. BBSplat represents the scene as a set of optimizable textured planar primitives with learnable RGB textures and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 David Svitov , Pietro Morerio , Lourdes Agapito , Alessio Del Bue

We present LangFlash, a feed-forward framework for 3D Language Gaussian Splatting that reconstructs 3D scenes parameterized by Gaussian primitives enriched with language-aligned semantic features from sparse unposed multi-view images.…

Computer Vision and Pattern Recognition · Computer Science 2026-05-25 Yilong Liu , Wanhua Li , Chen Zhu-Tian , Hanspeter Pfister

We propose DrivingForward, a feed-forward Gaussian Splatting model that reconstructs driving scenes from flexible surround-view input. Driving scene images from vehicle-mounted cameras are typically sparse, with limited overlap, and the…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Qijian Tian , Xin Tan , Yuan Xie , Lizhuang Ma

Gaussian Splatting has emerged as a powerful representation for high-quality, real-time 3D scene rendering. While recent works extend Gaussians with learnable textures to enrich visual appearance, existing approaches allocate a fixed square…

Computer Vision and Pattern Recognition · Computer Science 2026-01-15 Sheng-Chi Hsu , Ting-Yu Yen , Shih-Hsuan Hung , Hung-Kuo Chu

We present Splat-SAP, a feed-forward approach to render novel views of human-centered scenes from binocular cameras with large sparsity. Gaussian Splatting has shown its promising potential in rendering tasks, but it typically necessitates…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Boyao Zhou , Shunyuan Zheng , Zhanfeng Liao , Zihan Ma , Hanzhang Tu , Boning Liu , Yebin Liu

3D Gaussian Splatting (3DGS) has made significant strides in novel view synthesis but is limited by the substantial number of Gaussian primitives required, posing challenges for deployment on lightweight devices. Recent methods address this…

Computer Vision and Pattern Recognition · Computer Science 2025-04-09 Zhengqing Gao , Dongting Hu , Jia-Wang Bian , Huan Fu , Yan Li , Tongliang Liu , Mingming Gong , Kun Zhang

The advent of 3D Gaussian Splatting (3DGS) has recently brought about a revolution in the field of neural rendering, facilitating high-quality renderings at real-time speed. However, 3DGS heavily depends on the initialized point cloud…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 Kai Cheng , Xiaoxiao Long , Kaizhi Yang , Yao Yao , Wei Yin , Yuexin Ma , Wenping Wang , Xuejin Chen

Gaussian splatting has demonstrated excellent performance for view synthesis and scene reconstruction. The representation achieves photorealistic quality by optimizing the position, scale, color, and opacity of thousands to millions of 2D…

Computer Vision and Pattern Recognition · Computer Science 2025-02-27 Victor Rong , Jingxiang Chen , Sherwin Bahmani , Kiriakos N. Kutulakos , David B. Lindell

In this work, we revisit several key design choices of modern Transformer-based approaches for feed-forward 3D Gaussian Splatting (3DGS) prediction. We argue that the common practice of regressing Gaussian means as depths along camera rays…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Jiawei Ren , Michal Jan Tyszkiewicz , Jiahui Huang , Zan Gojcic