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Related papers: Generalizable Sparse-View 3D Reconstruction from U…

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Gaussian Splatting has achieved remarkable progress in multi-view surface reconstruction, yet it exhibits notable degradation when only few views are available. Although recent efforts alleviate this issue by enhancing multi-view…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Jimin Tang , Wenyuan Zhang , Junsheng Zhou , Zian Huang , Kanle Shi , Shenkun Xu , Yu-Shen Liu , Zhizhong Han

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

Compared with previous 3D reconstruction methods like Nerf, recent Generalizable 3D Gaussian Splatting (G-3DGS) methods demonstrate impressive efficiency even in the sparse-view setting. However, the promising reconstruction performance of…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Chuanrui Zhang , Yingshuang Zou , Zhuoling Li , Minmin Yi , Haoqian Wang

We propose WildSplatter, a feed-forward 3D Gaussian Splatting (3DGS) model for unconstrained images with unknown camera parameters and varying lighting conditions. 3DGS is an effective scene representation that enables high-quality,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Yuki Fujimura , Takahiro Kushida , Kazuya Kitano , Takuya Funatomi , Yasuhiro Mukaigawa

Prevailing 2D-centric visuomotor policies exhibit a pronounced deficiency in novel view generalization, as their reliance on static observations hinders consistent action mapping across unseen views. In response, we introduce GenSplat, a…

Robotics · Computer Science 2026-04-01 Sen Wang , Huaiyi Dong , Jingyi Tian , Jiayi Li , Zhuo Yang , Tongtong Cao , Anlin Chen , Shuang Wu , Le Wang , Sanping Zhou

Feed-forward 3D reconstruction from sparse, low-resolution (LR) images is a crucial capability for real-world applications, such as autonomous driving and embodied AI. However, existing methods often fail to recover fine texture details.…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Xinyuan Hu , Changyue Shi , Chuxiao Yang , Minghao Chen , Jiajun Ding , Tao Wei , Chen Wei , Zhou Yu , Min Tan

We propose a 3D novel sparse-view synthesis framework for unconstrained real-world scenarios that contain distractors. Unlike existing methods that primarily perform novel-view synthesis from a sparse set of constrained images without…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Wongi Park , Jordan A. James , Myeongseok Nam , Minjae Lee , Soomok Lee , Sang-Hyun Lee , William J. Beksi

Empowering 3D Gaussian Splatting with generalization ability is appealing. However, existing generalizable 3D Gaussian Splatting methods are largely confined to narrow-range interpolation between stereo images due to their heavy backbones,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Yunsong Wang , Tianxin Huang , Hanlin Chen , Gim Hee Lee

Surface reconstruction has been widely studied in computer vision and graphics. However, existing surface reconstruction works struggle to recover accurate scene geometry when the input views are extremely sparse. To address this issue, we…

Graphics · Computer Science 2025-11-26 Hanzhi Chang , Ruijie Zhu , Wenjie Chang , Mulin Yu , Yanzhe Liang , Jiahao Lu , Zhuoyuan Li , Tianzhu Zhang

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

Feed-forward 3D reconstruction offers substantial runtime advantages over per-scene optimization, which remains slow at inference and often fragile under sparse views. However, existing feed-forward methods still have potential for further…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Tianyu Chen , Wei Xiang , Kang Han , Yu Lu , Di Wu , Gaowen Liu , Ramana Rao Kompella

Recent advances in text-guided image editing and 3D Gaussian Splatting (3DGS) have enabled high-quality 3D scene manipulation. However, existing pipelines rely on iterative edit-and-fit optimization at test time, alternating between 2D…

Computer Vision and Pattern Recognition · Computer Science 2026-04-23 Haitao Huang , Shin-Fang Chng , Huangying Zhan , Qingan Yan , Yi Xu

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

Differentiable rendering techniques have recently shown promising results for free-viewpoint video synthesis of characters. However, such methods, either Gaussian Splatting or neural implicit rendering, typically necessitate per-subject…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Boyao Zhou , Shunyuan Zheng , Hanzhang Tu , Ruizhi Shao , Boning Liu , Shengping Zhang , Liqiang Nie , Yebin Liu

3D Gaussian Splatting (3DGS) has demonstrated impressive performance in 3D scene reconstruction. Beyond novel view synthesis, it shows great potential for multi-view surface reconstruction. Existing methods employ optimization-based…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Chensheng Dai , Shengjun Zhang , Min Chen , Yueqi Duan

3D scene reconstruction under unposed sparse viewpoints is a highly challenging yet practically important problem, especially in outdoor scenes due to complex lighting and scale variation. With extremely limited input views, directly…

Computer Vision and Pattern Recognition · Computer Science 2026-02-26 Beizhen Zhao , Sicheng Yu , Guanzhi Ding , Yu Hu , Hao Wang

Reconstructing semantic-aware 3D scenes from sparse views is a challenging yet essential research direction, driven by the demands of emerging applications such as virtual reality and embodied AI. Existing per-scene optimization methods…

Computer Vision and Pattern Recognition · Computer Science 2025-06-06 Yanbo Wang , Ziyi Wang , Wenzhao Zheng , Jie Zhou , Jiwen Lu

Recent progress in feed-forward 3D Gaussian Splatting (3DGS) has notably improved rendering quality. However, the spatially uniform and highly redundant 3DGS map generated by previous feed-forward 3DGS methods limits their integration into…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Zicheng Zhang , Xiangting Meng , Ke Wu , Wenchao Ding

Three-dimensional scene reconstruction from sparse-view satellite images is a long-standing and challenging task. While 3D Gaussian Splatting (3DGS) and its variants have recently attracted attention for its high efficiency, existing…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Xuejun Huang , Xinyi Liu , Yi Wan , Zhi Zheng , Bin Zhang , Mingtao Xiong , Yingying Pei , Yongjun Zhang

Recovering 3D information from scenes via multi-view stereo reconstruction (MVS) and novel view synthesis (NVS) is inherently challenging, particularly in scenarios involving sparse-view setups. The advent of 3D Gaussian Splatting (3DGS)…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Shubhendu Jena , Shishir Reddy Vutukur , Adnane Boukhayma
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