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Related papers: DepthSplat: Connecting Gaussian Splatting and Dept…

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Reconstructing transparent surfaces is essential for tasks such as robotic manipulation in labs, yet it poses a significant challenge for 3D reconstruction techniques like 3D Gaussian Splatting (3DGS). These methods often encounter a…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Mingwei Li , Pu Pang , Hehe Fan , Hua Huang , Yi Yang

Previous surface reconstruction methods either suffer from low geometric accuracy or lengthy training times when dealing with real-world complex dynamic scenes involving multi-person activities, and human-object interactions. To tackle the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Shuo Wang , Binbin Huang , Ruoyu Wang , Shenghua Gao

3D Shape represented as point cloud has achieve advancements in multimodal pre-training to align image and language descriptions, which is curial to object identification, classification, and retrieval. However, the discrete representations…

Computer Vision and Pattern Recognition · Computer Science 2024-02-14 Haoyuan Li , Yanpeng Zhou , Yihan Zeng , Hang Xu , Xiaodan Liang

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

Accurate 3D human pose estimation is fundamental for applications such as augmented reality and human-robot interaction. State-of-the-art multi-view methods learn to fuse predictions across views by training on large annotated datasets,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Laura Bragagnolo , Leonardo Barcellona , Stefano Ghidoni

Depth estimation is a fundamental task in 3D geometry. While stereo depth estimation can be achieved through triangulation methods, it is not as straightforward for monocular methods, which require the integration of global and local…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Jinchang Zhang , Ningning Xu , Hao Zhang , Guoyu Lu

Novel View Synthesis (NVS) from sparse views presents a formidable challenge in 3D reconstruction, where limited multi-view constraints lead to severe overfitting, geometric distortion, and fragmented scenes. While 3D Gaussian Splatting…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Yu Ma , Guoliang Wei , Haihong Xiao , Yue Cheng

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

Object-level 3D reconstruction play important roles across domains such as cultural heritage digitization, industrial manufacturing, and virtual reality. However, existing Gaussian Splatting-based approaches generally rely on full-scene…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Shuai Guo , Ao Guo , Junchao Zhao , Qi Chen , Yuxiang Qi , Zechuan Li , Dong Chen , Tianjia Shao , Mingliang Xu

Gaussian Splatting (GS) has emerged as an efficient approach for high-quality novel view synthesis. While early GS variants struggled to accurately model the scene's geometry, recent advancements constraining the Gaussians' spread and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-27 David Recasens , Robert Maier , Aljaz Bozic , Stephane Grabli , Javier Civera , Tony Tung , Edmond Boyer

In the rapidly evolving field of 3D reconstruction, 3D Gaussian Splatting (3DGS) and 2D Gaussian Splatting (2DGS) represent significant advancements. Although 2DGS compresses 3D Gaussian primitives into 2D Gaussian surfels to effectively…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Zhuoxiao Li , Shanliang Yao , Yijie Chu , Angel F. Garcia-Fernandez , Yong Yue , Eng Gee Lim , Xiaohui Zhu

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

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

Recently, 3D Gaussian Splatting (3DGS) has attracted widespread attention due to its high-quality rendering, and ultra-fast training and rendering speed. However, due to the unstructured and irregular nature of Gaussian point clouds, it is…

Computer Vision and Pattern Recognition · Computer Science 2025-01-13 Danpeng Chen , Hai Li , Weicai Ye , Yifan Wang , Weijian Xie , Shangjin Zhai , Nan Wang , Haomin Liu , Hujun Bao , Guofeng Zhang

Depth maps are widely used in feed-forward 3D Gaussian Splatting (3DGS) pipelines by unprojecting them into 3D point clouds for novel view synthesis. This approach offers advantages such as efficient training, the use of known camera poses,…

Computer Vision and Pattern Recognition · Computer Science 2025-06-06 Duochao Shi , Weijie Wang , Donny Y. Chen , Zeyu Zhang , Jia-Wang Bian , Bohan Zhuang , Chunhua Shen

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

We present TokenSplat, a feed-forward framework for joint 3D Gaussian reconstruction and camera pose estimation from unposed multi-view images. At its core, TokenSplat introduces a Token-aligned Gaussian Prediction module that aligns…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Yihui Li , Chengxin Lv , Zichen Tang , Hongyu Yang , Di Huang

Recent developments in 3D Gaussian Splatting have made significant advances in surface reconstruction. However, scaling these methods to large-scale scenes remains challenging due to high computational demands and the complex dynamic…

Graphics · Computer Science 2025-06-24 Shihan Chen , Zhaojin Li , Zeyu Chen , Qingsong Yan , Gaoyang Shen , Ran Duan

We introduce Dr. Splat, a novel approach for open-vocabulary 3D scene understanding leveraging 3D Gaussian Splatting. Unlike existing language-embedded 3DGS methods, which rely on a rendering process, our method directly associates…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Kim Jun-Seong , GeonU Kim , Kim Yu-Ji , Yu-Chiang Frank Wang , Jaesung Choe , Tae-Hyun Oh

This paper presents RoGSplat, a novel approach for synthesizing high-fidelity novel views of unseen human from sparse multi-view images, while requiring no cumbersome per-subject optimization. Unlike previous methods that typically struggle…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Junjin Xiao , Qing Zhang , Yonewei Nie , Lei Zhu , Wei-Shi Zheng
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