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Tracking non-rigidly deforming scenes using range sensors has numerous applications including computer vision, AR/VR, and robotics. However, due to occlusions and physical limitations of range sensors, existing methods only handle the…

Computer Vision and Pattern Recognition · Computer Science 2021-05-06 Yang Li , Hikari Takehara , Takafumi Taketomi , Bo Zheng , Matthias Nießner

While dynamic novel view synthesis from 2D videos has seen progress, achieving efficient reconstruction and rendering of dynamic scenes remains a challenging task. In this paper, we introduce Disentangled 4D Gaussian Splatting…

Graphics · Computer Science 2025-10-31 Hao Feng , Hao Sun , Wei Xie , Zhi Zuo , Zhengzhe Liu

Humans naturally perceive a 3D scene in front of them through accumulation of information obtained from multiple interconnected projections of the scene and by interpreting their correspondence. This phenomenon has inspired artificial…

Computer Vision and Pattern Recognition · Computer Science 2018-11-20 Amirreza Farnoosh , Sarah Ostadabbas

Visual navigation and three-dimensional (3D) scene reconstruction are essential for robotics to interact with the surrounding environment. Large-scale scenes and critical camera motions are great challenges facing the research community to…

Computer Vision and Pattern Recognition · Computer Science 2021-09-21 Qi Cai , Lilian Zhang , Yuanxin Wu , Wenxian Yu , Dewen Hu

Reconstructing and predicting dynamic 3D scenes from multi-view videos is a foundational task for robotics, AR/VR, and digital twins. Recent physics-informed Gaussian Splatting methods achieve impressive future frame extrapolation but lack…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Denis Gridusov , Maxim Popov , Sergey Kolyubin

Understanding dynamic 4D scenes from an egocentric perspective-modeling changes in 3D spatial structure over time-is crucial for human-machine interaction, autonomous navigation, and embodied intelligence. While existing egocentric datasets…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Junsheng Huang , Shengyu Hao , Bocheng Hu , Hongwei Wang , Gaoang Wang

Recent advances in 4D generation mainly focus on generating 4D content by distilling pre-trained text or single-view image-conditioned models. It is inconvenient for them to take advantage of various off-the-shelf 3D assets with multi-view…

Computer Vision and Pattern Recognition · Computer Science 2024-09-10 Yanqin Jiang , Chaohui Yu , Chenjie Cao , Fan Wang , Weiming Hu , Jin Gao

We present a scalable 3D reconstruction model that addresses a critical limitation in offline feed-forward methods: their computational and memory requirements grow quadratically w.r.t. the number of input images. Our approach is built on…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Sven Elflein , Ruilong Li , Sérgio Agostinho , Zan Gojcic , Laura Leal-Taixé , Qunjie Zhou , Aljosa Osep

Gait, the walking pattern of individuals, is one of the important biometrics modalities. Most of the existing gait recognition methods take silhouettes or articulated body models as gait features. These methods suffer from degraded…

Computer Vision and Pattern Recognition · Computer Science 2019-09-10 Ziyuan Zhang , Luan Tran , Feng Liu , Xiaoming Liu

Volumetric visualization has long been dominated by Direct Volume Rendering (DVR), which operates on dense voxel grids and suffers from limited scalability as resolution and interactivity demands increase. Recent advances in 3D Gaussian…

Graphics · Computer Science 2026-04-15 Yuxuan Wang , Qibiao Li , Youcheng Cai

Achieving truly practical dynamic 3D reconstruction requires online operation, global pose and map consistency, detailed appearance modeling, and the flexibility to handle both RGB and RGB-D inputs. However, existing SLAM methods typically…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Shi Chen , Erik Sandström , Sandro Lombardi , Siyuan Li , Martin R. Oswald

Achieving robust and precise pose estimation in dynamic scenes is a significant research challenge in Visual Simultaneous Localization and Mapping (SLAM). Recent advancements integrating Gaussian Splatting into SLAM systems have proven…

Robotics · Computer Science 2024-11-14 Yueming Xu , Haochen Jiang , Zhongyang Xiao , Jianfeng Feng , Li Zhang

Foundation models for 3D vision have recently demonstrated remarkable capabilities in 3D perception. However, scaling these models to long-sequence image inputs remains a significant challenge due to inference-time inefficiency. In this…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 You Shen , Zhipeng Zhang , Yansong Qu , Xiawu Zheng , Jiayi Ji , Shengchuan Zhang , Liujuan Cao

Integrating open-vocabulary semantic information into dynamic 3D scene representations is essential for long-term embodied scene understanding. However, existing methods often suffer from fragile instance association due to incomplete…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Luzhou Ge , Xiangyu Zhu , Jinyan Liu , Xuesong Li

Estimating 6D poses of objects is an essential computer vision task. However, most conventional approaches rely on camera data from a single perspective and therefore suffer from occlusions. We overcome this issue with our novel multi-view…

Computer Vision and Pattern Recognition · Computer Science 2022-08-03 Fabian Duffhauss , Tobias Demmler , Gerhard Neumann

Recent developments in 2D visual generation have been remarkably successful. However, 3D and 4D generation remain challenging in real-world applications due to the lack of large-scale 4D data and effective model design. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2024-11-06 Yuyang Zhao , Chung-Ching Lin , Kevin Lin , Zhiwen Yan , Linjie Li , Zhengyuan Yang , Jianfeng Wang , Gim Hee Lee , Lijuan Wang

Reconstructing clean, distractor-free 3D scenes from real-world captures remains a significant challenge, particularly in highly dynamic and cluttered settings such as egocentric videos. To tackle this problem, we introduce DeGauss, a…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Rui Wang , Quentin Lohmeyer , Mirko Meboldt , Siyu Tang

Driven by the advancement of 3D devices, stereo vision tasks including stereo matching and stereo conversion have emerged as a critical research frontier. Contemporary stereo vision backbones typically rely on either monocular depth…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Ziyang Chen , Yansong Qu , You Shen , Xuan Cheng , Liujuan Cao

Recent feed-forward 3D gaussian splatting methods have made dramatic progress on individual aspects of 3D scene reconstruction, but no existing method jointly addresses dynamic content, multi-view input, and unknown camera poses in a single…

Computer Vision and Pattern Recognition · Computer Science 2026-05-22 Matteo Balice , Yanik Kunzi , Chenyangguang Zhang , Matteo Matteucci , Marc Pollefeys , Sungwhan Hong

The availability of large-scale multimodal datasets and advancements in diffusion models have significantly accelerated progress in 4D content generation. Most prior approaches rely on multiple image or video diffusion models, utilizing…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Hanwen Liang , Yuyang Yin , Dejia Xu , Hanxue Liang , Zhangyang Wang , Konstantinos N. Plataniotis , Yao Zhao , Yunchao Wei