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Reconstructing Dynamic 3D Gaussian Splatting (3DGS) from low-framerate RGB videos is challenging. This is because large inter-frame motions will increase the uncertainty of the solution space. For example, one pixel in the first frame might…

Computer Vision and Pattern Recognition · Computer Science 2025-12-12 Junhao He , Jiaxu Wang , Jia Li , Mingyuan Sun , Qiang Zhang , Jiahang Cao , Ziyi Zhang , Yi Gu , Jingkai Sun , Renjing Xu

3D Gaussian Splatting (3DGS) has become an emerging tool for dynamic scene reconstruction. However, existing methods focus mainly on extending static 3DGS into a time-variant representation, while overlooking the rich motion information…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Zhiyang Guo , Wengang Zhou , Li Li , Min Wang , Houqiang Li

View-predictive generative models provide strong priors for lifting object-centric images and videos into 3D and 4D through rendering and score distillation objectives. A question then remains: what about lifting complete multi-object…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Wen-Hsuan Chu , Lei Ke , Katerina Fragkiadaki

Recent advancements in video semantic segmentation have made substantial progress by exploiting temporal correlations. Nevertheless, persistent challenges, including redundant computation and the reliability of the feature propagation…

Computer Vision and Pattern Recognition · Computer Science 2024-12-30 Yaoyan Zheng , Hongyu Yang , Di Huang

Recently, 3D Gaussian Splatting and its derivatives have achieved significant breakthroughs in large-scale scene reconstruction. However, how to efficiently and stably achieve high-quality geometric fidelity remains a core challenge. To…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Kehua Chen , Tianlu Mao , Xinzhu Ma , Hao Jiang , Zehao Li , Zihan Liu , Shuqin Gao , Honglong Zhao , Feng Dai , Yucheng Zhang , Zhaoqi Wang

Decompositional reconstruction of 3D scenes, with complete shapes and detailed texture of all objects within, is intriguing for downstream applications but remains challenging, particularly with sparse views as input. Recent approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Junfeng Ni , Yu Liu , Ruijie Lu , Zirui Zhou , Song-Chun Zhu , Yixin Chen , Siyuan Huang

Dynamic scene reconstruction is a long-term challenge in 3D vision. Recent methods extend 3D Gaussian Splatting to dynamic scenes via additional deformation fields and apply explicit constraints like motion flow to guide the deformation.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 DaDong Jiang , Zhihui Ke , Xiaobo Zhou , Zhi Hou , Xianghui Yang , Wenbo Hu , Tie Qiu , Chunchao Guo

Novel view synthesis has shown rapid progress recently, with methods capable of producing increasingly photorealistic results. 3D Gaussian Splatting has emerged as a promising method, producing high-quality renderings of scenes and enabling…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Richard Shaw , Michal Nazarczuk , Jifei Song , Arthur Moreau , Sibi Catley-Chandar , Helisa Dhamo , Eduardo Perez-Pellitero

We address the problem of extending the capabilities of vision foundation models such as DINO, SAM, and CLIP, to 3D tasks. Specifically, we introduce a novel method to uplift 2D image features into Gaussian Splatting representations of 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Juliette Marrie , Romain Menegaux , Michael Arbel , Diane Larlus , Julien Mairal

3D reconstruction and novel view synthesis are critical for validating autonomous driving systems and training advanced perception models. Recent self-supervised methods have gained significant attention due to their cost-effectiveness and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-17 Xiao Tang , Guirong Zhuo , Cong Wang , Boyuan Zheng , Minqing Huang , Lianqing Zheng , Long Chen , Shouyi Lu

We introduce ShapeGaussian, a high-fidelity, template-free method for 4D human reconstruction from casual monocular videos. Generic reconstruction methods lacking robust vision priors, such as 4DGS, struggle to capture high-deformation…

Computer Vision and Pattern Recognition · Computer Science 2026-02-06 Zhenxiao Liang , Ning Zhang , Youbao Tang , Ruei-Sung Lin , Qixing Huang , Peng Chang , Jing Xiao

Immersive video offers a 6-Dof-free viewing experience, potentially playing a key role in future video technology. Recently, 4D Gaussian Splatting has gained attention as an effective approach for immersive video due to its high rendering…

Computer Vision and Pattern Recognition · Computer Science 2025-05-13 Hao Li , Sicheng Li , Xiang Gao , Abudouaihati Batuer , Lu Yu , Yiyi Liao

4D content generation has achieved remarkable progress recently. However, existing methods suffer from long optimization times, a lack of motion controllability, and a low quality of details. In this paper, we introduce DreamGaussian4D…

Computer Vision and Pattern Recognition · Computer Science 2024-06-11 Jiawei Ren , Liang Pan , Jiaxiang Tang , Chi Zhang , Ang Cao , Gang Zeng , Ziwei Liu

In this work, we introduce a generative approach for pose-free (without camera parameters) reconstruction of 360 scenes from a sparse set of 2D images. Pose-free scene reconstruction from incomplete, pose-free observations is usually…

Computer Vision and Pattern Recognition · Computer Science 2025-10-13 Soumava Paul , Prakhar Kaushik , Alan Yuille

Reconstructing dynamic 3D scenes from monocular videos is a fundamental yet highly challenging task, as real-world motions often involve both long-term smooth transformations and short-term complex deformations. Existing methods either…

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

Monocular dynamic reconstruction is a challenging and long-standing vision problem due to the highly ill-posed nature of the task. Existing approaches depend on templates, are effective only in quasi-static scenes, or fail to model 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Qianqian Wang , Vickie Ye , Hang Gao , Weijia Zeng , Jake Austin , Zhengqi Li , Angjoo Kanazawa

Reconstructing and segmenting scenes from unconstrained photo collections obtained from the Internet is a novel but challenging task. Unconstrained photo collections are easier to get than well-captured photo collections. These…

Computer Vision and Pattern Recognition · Computer Science 2025-07-11 Yongtang Bao , Chengjie Tang , Yuze Wang , Haojie Li

We have recently seen great progress in 3D scene reconstruction through explicit point-based 3D Gaussian Splatting (3DGS), notable for its high quality and fast rendering speed. However, reconstructing dynamic scenes such as complex human…

Computer Vision and Pattern Recognition · Computer Science 2025-03-10 Chao Zhang , Yifeng Zhou , Shuheng Wang , Wenfa Li , Degang Wang , Yi Xu , Shaohui Jiao

3D Gaussian Splatting (3DGS) demonstrates unparalleled superior performance in 3D scene reconstruction. However, 3DGS heavily relies on the sharp images. Fulfilling this requirement can be challenging in real-world scenarios especially when…

Computer Vision and Pattern Recognition · Computer Science 2024-12-25 Yijia Guo , Liwen Hu , Yuanxi Bai , Jiawei Yao , Lei Ma , Tiejun Huang

This paper proposes a novel framework for large-scale scene reconstruction based on 3D Gaussian splatting (3DGS) and aims to address the scalability and accuracy challenges faced by existing methods. For tackling the scalability issue, we…

Computer Vision and Pattern Recognition · Computer Science 2024-09-25 Hanyue Zhang , Zhiliu Yang , Xinhe Zuo , Yuxin Tong , Ying Long , Chen Liu