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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

While existing feed-forward Gaussian splatting models offer computational efficiency and can generalize to sparse view settings, their performance is fundamentally constrained by relying on a single forward pass for inference. We propose…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Haofei Xu , Daniel Barath , Andreas Geiger , Marc Pollefeys

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

Recent advances in 3D representations, such as Neural Radiance Fields and 3D Gaussian Splatting, have greatly improved realistic scene modeling and novel-view synthesis. However, achieving controllable and consistent editing in dynamic 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Kai He , Chin-Hsuan Wu , Igor Gilitschenski

Feed-forward 3D Gaussian Splatting models offer fast single-pass reconstruction,but scaling them to match per-scene optimization quality is fundamentally hindered by the scarcity of large-scale 3D annotations. A practical compromise is…

Computer Vision and Pattern Recognition · Computer Science 2026-05-25 Yuke Li , Weihang Liu , Cheng Zhang , Yuefeng Zhang , Jiadi Cui , Zixuan Wang , Junran Ding , Haoyu Wu , Yujiao Shi , Jingyi Yu , Xin Lou

Reconstructing 3D scenes from sparse, unposed images remains challenging under real-world conditions with varying illumination and transient occlusions. Existing methods rely on scene-specific optimization using appearance embeddings or…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Vinayak Gupta , Chih-Hao Lin , Shenlong Wang , Anand Bhattad , Jia-Bin Huang

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

3D Gaussian Splatting based 3D editing has demonstrated impressive performance in recent years. However, the multi-view editing often exhibits significant local inconsistency, especially in areas of non-rigid deformation, which lead to…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Minghao Wen , Shengjie Wu , Kangkan Wang , Dong Liang

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

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

The creation of 3D scenes has traditionally been both labor-intensive and costly, requiring designers to meticulously configure 3D assets and environments. Recent advancements in generative AI, including text-to-3D and image-to-3D methods,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Ziyang Yan , Yihua Shao , Minwen Liao , Siyu Chen , Nan Wang , Muyuan Lin , Jenq-Neng Hwang , Hao Zhao , Fabio Remondino , Lei Li

Feed-forward 3D Gaussian Splatting (3DGS) has emerged as a highly effective solution for novel view synthesis. Existing methods predominantly rely on a \emph{pixel-aligned} Gaussian prediction paradigm, where each 2D pixel is mapped to a 3D…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Weijie Wang , Yeqing Chen , Zeyu Zhang , Hengyu Liu , Haoxiao Wang , Zhiyuan Feng , Wenkang Qin , Feng Chen , Zheng Zhu , Donny Y. Chen , Bohan Zhuang

Feed-forward 3D Gaussian Splatting (3DGS) enables efficient one-pass scene reconstruction, providing 3D representations for novel view synthesis without per-scene optimization. However, existing methods typically predict pixel-aligned…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Jongmin Park , Minh-Quan Viet Bui , Juan Luis Gonzalez Bello , Jaeho Moon , Jihyong Oh , Munchurl Kim

3D Gaussian Splatting (3DGS) has shown remarkable performance in novel view synthesis. However, its rendering quality deteriorates with sparse inphut views, leading to distorted content and reduced details. This limitation hinders its…

Computer Vision and Pattern Recognition · Computer Science 2025-01-22 Zongqi He , Zhe Xiao , Kin-Chung Chan , Yushen Zuo , Jun Xiao , Kin-Man Lam

This paper presents a pose-free, feed-forward 3D Gaussian Splatting (3DGS) framework designed to handle unfavorable input views. A common rendering setup for training feed-forward approaches places a 3D object at the world origin and…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Yuki Fujimura , Takahiro Kushida , Kazuya Kitano , Takuya Funatomi , Yasuhiro Mukaigawa

Radiance fields represented by 3D Gaussians excel at synthesizing novel views, offering both high training efficiency and fast rendering. However, with sparse input views, the lack of multi-view consistency constraints results in poorly…

Computer Vision and Pattern Recognition · Computer Science 2025-08-27 Yuru Xiao , Deming Zhai , Wenbo Zhao , Kui Jiang , Junjun Jiang , Xianming Liu

3D Gaussian Splatting (3DGS) has recently emerged as a promising approach in novel view synthesis, combining photorealistic rendering with real-time efficiency. However, its success heavily relies on dense camera coverage; under sparse-view…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Jiashu Li , Xumeng Han , Zhaoyang Wei , Zipeng Wang , Kuiran Wang , Guorong Li , Zhenjun Han , Jianbin Jiao

Recently, 3D Gaussian Splatting (3DGS) has demonstrated remarkable success in 3D reconstruction and novel view synthesis. However, reconstructing 3D scenes from sparse viewpoints remains highly challenging due to insufficient visual…

Computer Vision and Pattern Recognition · Computer Science 2025-09-24 Zhaorui Wang , Yi Gu , Deming Zhou , Renjing Xu

We consider the problem of novel view synthesis from unposed images in a single feed-forward. Our framework capitalizes on fast speed, scalability, and high-quality 3D reconstruction and view synthesis capabilities of 3DGS, where we further…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Sunghwan Hong , Jaewoo Jung , Heeseong Shin , Jisang Han , Jiaolong Yang , Chong Luo , Seungryong Kim

Feed-forward 3D Gaussian Splatting (3DGS) has recently demonstrated promising results for novel view synthesis (NVS) from sparse input views, particularly under narrow-baseline conditions. However, its performance significantly degrades in…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Xiaohan Lu , Jiaye Fu , Jiaqi Zhang , Zetian Song , Chuanmin Jia , Siwei Ma