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Reconstructing dynamic 3D scenes from blurry monocular videos is challenging as motion-induced blur entangles object motion and geometry, hindering geometric consistency. We present Kinematics-GS, a kinematics-aware framework that models…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Yeon-Ji Song , Kiyoung Kwon , Junoh Lee , Jin-Hwa Kim , Byoung-Tak Zhang

Recent 4D reconstruction methods have yielded impressive results but rely on sharp videos as supervision. However, motion blur often occurs in videos due to camera shake and object movement, while existing methods render blurry results when…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Renlong Wu , Zhilu Zhang , Mingyang Chen , Zifei Yan , Wangmeng Zuo

High-quality scene reconstruction and novel view synthesis based on Gaussian Splatting (3DGS) typically require steady, high-quality photographs, often impractical to capture with handheld cameras. We present a method that adapts to camera…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Otto Seiskari , Jerry Ylilammi , Valtteri Kaatrasalo , Pekka Rantalankila , Matias Turkulainen , Juho Kannala , Esa Rahtu , Arno Solin

We present a method that simultaneously addresses the tasks of dynamic scene novel-view synthesis and six degree-of-freedom (6-DOF) tracking of all dense scene elements. We follow an analysis-by-synthesis framework, inspired by recent work…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Jonathon Luiten , Georgios Kopanas , Bastian Leibe , Deva Ramanan

Event cameras offer promising advantages such as high dynamic range and low latency, making them well-suited for challenging lighting conditions and fast-moving scenarios. However, reconstructing 3D scenes from raw event streams is…

Computer Vision and Pattern Recognition · Computer Science 2024-10-11 Jiaxu Wang , Junhao He , Ziyi Zhang , Mingyuan Sun , Jingkai Sun , Renjing Xu

Dynamic Gaussian Splatting approaches have achieved remarkable performance for 4D scene reconstruction. However, these approaches rely on dense-frame video sequences for photorealistic reconstruction. In real-world scenarios, due to…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Changyue Shi , Chuxiao Yang , Xinyuan Hu , Minghao Chen , Wenwen Pan , Yan Yang , Jiajun Ding , Zhou Yu , Jun Yu

3D Gaussian Splatting (3DGS) has gained significant attention for its real-time, photo-realistic rendering in novel-view synthesis and 3D modeling. However, existing methods struggle with accurately modeling in-the-wild scenes affected by…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Chuanyu Fu , Guanying Chen , Yuqi Zhang , Kunbin Yao , Yuan Xiong , Chuan Huang , Shuguang Cui , Yasuyuki Matsushita , Xiaochun Cao

Decoupling lighting from geometry using unconstrained photo collections is notoriously challenging. Solving it would benefit many users as creating complex 3D assets takes days of manual labor. Many previous works have attempted to address…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Joanna Kaleta , Kacper Kania , Tomasz Trzcinski , Marek Kowalski

3D Gaussian Splatting has shown fast and high-quality rendering results in static scenes by leveraging dense 3D prior and explicit representations. Unfortunately, the benefits of the prior and representation do not involve novel view…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Junoh Lee , Chang-Yeon Won , Hyunjun Jung , Inhwan Bae , Hae-Gon Jeon

Surgical reconstruction of dynamic tissues from endoscopic videos is a crucial technology in robot-assisted surgery. The development of Neural Radiance Fields (NeRFs) has greatly advanced deformable tissue reconstruction, achieving…

Computer Vision and Pattern Recognition · Computer Science 2025-11-03 Wenfeng Huang , Xiangyun Liao , Yinling Qian , Hao Liu , Yongming Yang , Wenjing Jia , Qiong Wang

3D Gaussian splatting (3DGS) offers the capability to achieve real-time high quality 3D scene rendering. However, 3DGS assumes that the scene is in a clear medium environment and struggles to generate satisfactory representations in…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Haoran Wang , Nantheera Anantrasirichai , Fan Zhang , David Bull

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

3D Gaussian Splatting (GS) enables highly photorealistic scene reconstruction from posed image sequences but struggles with viewpoint extrapolation due to its anisotropic nature, leading to overfitting and poor generalization, particularly…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Shuohan Tao , Boyao Zhou , Hanzhang Tu , Yuwang Wang , Yebin Liu

We introduce GeoGS3D, a novel two-stage framework for reconstructing detailed 3D objects from single-view images. Inspired by the success of pre-trained 2D diffusion models, our method incorporates an orthogonal plane decomposition…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Qijun Feng , Zhen Xing , Zuxuan Wu , Yu-Gang Jiang

4D reconstruction from casually captured monocular videos is challenging due to inherent ambiguity in reconstructing dynamic 3D geometry. To address this challenge, we introduce Robust Dynamic Gaussian Splatting (RoDyGS), a method that…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Junmyeong Lee , Hoseung Choi , Yoonwoo Jeong , Minsu Cho

This paper tackles the challenge of recovering 4D dynamic scenes from videos captured by as few as four portable cameras. Learning to model scene dynamics for temporally consistent novel-view rendering is a foundational task in computer…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Junsheng Zhou , Zhifan Yang , Liang Han , Wenyuan Zhang , Kanle Shi , Shenkun Xu , Yu-Shen Liu

We present DGGS, a novel framework that addresses the previously unexplored challenge: $\textbf{Distractor-free Generalizable 3D Gaussian Splatting}$ (3DGS). It mitigates 3D inconsistency and training instability caused by distractor data…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Yanqi Bao , Jing Liao , Jing Huo , Yang Gao

We introduce a novel method for dynamic free-view synthesis of an ambient scenes from a monocular capture bringing a immersive quality to the viewing experience. Our method builds upon the recent advancements in 3D Gaussian Splatting (3DGS)…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Meng-Li Shih , Jia-Bin Huang , Changil Kim , Rajvi Shah , Johannes Kopf , Chen Gao

3D Gaussian Splatting (3DGS) is a highly deployable real-time method for novel view synthesis. In practice, it requires a universal, consistent control mechanism that adjusts the trade-off between rendering quality and model compression…

Computer Vision and Pattern Recognition · Computer Science 2025-11-10 Fengdi Zhang , Yibao Sun , Hongkun Cao , Ruqi Huang

Recently, 3D Gaussian Splatting (3DGS) has emerged as an efficient approach for accurately representing scenes. However, despite its superior novel view synthesis capabilities, extracting the geometry of the scene directly from the Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Yaniv Wolf , Amit Bracha , Ron Kimmel
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