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Related papers: Occlusion-Aware Temporally Consistent Amodal Compl…

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With the widespread adoption of autonomous vehicles and robotics, amodal completion, which reconstructs the occluded parts of people and objects in an image, has become increasingly crucial. Just as humans infer hidden regions based on…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Heecheol Yun , Eunho Yang

Reconstructing high-fidelity and animatable 3D head avatars from monocular videos remains a challenging yet essential task. Existing methods based on 3D Gaussian Splatting typically bind Gaussians to mesh triangles and model deformations…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Jiankuo Zhao , Xiangyu Zhu , Zidu Wang , Zhen Lei

Understanding dynamic scenes from casual videos is critical for scalable robot learning, yet four-dimensional (4D) reconstruction under strictly monocular settings remains highly ill-posed. To address this challenge, our key insight is that…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Can Li , Jie Gu , Jingmin Chen , Fangzhou Qiu , Lei Sun

The reconstruction of dynamic 3D scenes using 3D Gaussian Splatting has shown significant promise. A key challenge, however, remains in modeling realistic motion, as most methods fail to align the motion of Gaussians with real-world…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Junoh Lee , Junmyeong Lee , Yeon-Ji Song , Inhwan Bae , Jisu Shin , Hae-Gon Jeon , Jin-Hwa Kim

Capturing the interactions between humans and their environment in 3D is important for many applications in robotics, graphics, and vision. Recent works to reconstruct the 3D human and object from a single RGB image do not have consistent…

Computer Vision and Pattern Recognition · Computer Science 2023-11-01 Xianghui Xie , Bharat Lal Bhatnagar , Gerard Pons-Moll

Online reconstruction of dynamic scenes is significant as it enables learning scenes from live-streaming video inputs, while existing offline dynamic reconstruction methods rely on recorded video inputs. However, previous online…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Youngsik Yun , Jeongmin Bae , Hyunseung Son , Seoha Kim , Hahyun Lee , Gun Bang , Youngjung Uh

Egocentric video provides a unique view into human perception and interaction, with growing relevance for augmented reality, robotics, and assistive technologies. However, rapid camera motion and complex scene dynamics pose major challenges…

Computer Vision and Pattern Recognition · Computer Science 2026-04-28 Jan Warchocki , Xi Wang , Jonas Kulhanek , Jan van Gemert

Egocentric scenes exhibit frequent occlusions, varied viewpoints, and dynamic interactions compared to typical scene understanding tasks. Occlusions and varied viewpoints can lead to multi-view semantic inconsistencies, while dynamic…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Di Li , Jie Feng , Jiahao Chen , Weisheng Dong , Guanbin Li , Guangming Shi , Licheng Jiao

Human motion reconstruction from monocular videos is a fundamental challenge in computer vision, with broad applications in AR/VR, robotics, and digital content creation, but remains challenging under frequent occlusions in real-world…

Computer Vision and Pattern Recognition · Computer Science 2026-01-26 Zhiyin Qian , Siwei Zhang , Bharat Lal Bhatnagar , Federica Bogo , Siyu Tang

We introduce a fully automatic pipeline for dynamic scene reconstruction from casually captured monocular RGB videos. Rather than designing a new scene representation, we enhance the priors that drive Dynamic Gaussian Splatting. Video…

Computer Vision and Pattern Recognition · Computer Science 2025-12-15 Meng-Li Shih , Ying-Huan Chen , Yu-Lun Liu , Brian Curless

We present the first marker-less approach for temporally coherent 3D performance capture of a human with general clothing from monocular video. Our approach reconstructs articulated human skeleton motion as well as medium-scale non-rigid…

Computer Vision and Pattern Recognition · Computer Science 2018-02-26 Weipeng Xu , Avishek Chatterjee , Michael Zollhöfer , Helge Rhodin , Dushyant Mehta , Hans-Peter Seidel , Christian Theobalt

While novel view synthesis for dynamic scenes has made significant progress, capturing skeleton models of objects and re-posing them remains a challenging task. To tackle this problem, in this paper, we propose a novel approach to…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Diwen Wan , Yuxiang Wang , Ruijie Lu , Gang Zeng

Free-moving object reconstruction from monocular video remains challenging, particularly without reliable pose or depth cues and under arbitrary object motion. We introduce OnlineSplatter, a novel online feed-forward framework generating…

Computer Vision and Pattern Recognition · Computer Science 2025-10-24 Mark He Huang , Lin Geng Foo , Christian Theobalt , Ying Sun , De Wen Soh

We present Orientation-anchored Gaussian Splatting (OriGS), a novel framework for high-quality 4D reconstruction from casually captured monocular videos. While recent advances extend 3D Gaussian Splatting to dynamic scenes via various…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Junyi Wu , Jiachen Tao , Haoxuan Wang , Gaowen Liu , Ramana Rao Kompella , Yan Yan

Realistic reconstruction of dynamic 4D scenes from monocular videos is essential for understanding the physical world. Despite recent progress in neural rendering, existing methods often struggle to recover accurate 3D geometry and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Haoran Zhou , Gim Hee Lee

Recent advances in generalizable 3D Gaussian Splatting have demonstrated promising results in real-time high-fidelity rendering without per-scene optimization, yet existing approaches still struggle to handle unfamiliar visual content…

Computer Vision and Pattern Recognition · Computer Science 2025-05-22 Yifan Liu , Keyu Fan , Weihao Yu , Chenxin Li , Hao Lu , Yixuan Yuan

Recent advancements in zero-shot video diffusion models have shown promise for text-driven video editing, but challenges remain in achieving high temporal consistency. To address this, we introduce Video-3DGS, a 3D Gaussian Splatting…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Inkyu Shin , Qihang Yu , Xiaohui Shen , In So Kweon , Kuk-Jin Yoon , Liang-Chieh Chen

Accurately analyzing the motion parts and their motion attributes in dynamic environments is crucial for advancing key areas such as embodied intelligence. Addressing the limitations of existing methods that rely on dense multi-view images…

Computer Vision and Pattern Recognition · Computer Science 2025-07-14 Hongyi Zhou , Yulan Guo , Xiaogang Wang , Kai Xu

3D Gaussian Splatting (3DGS) has shown remarkable potential for static scene reconstruction, and recent advancements have extended its application to dynamic scenes. However, the quality of reconstructions depends heavily on high-quality…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Yiren Lu , Yunlai Zhou , Disheng Liu , Tuo Liang , Yu Yin

Rendering the visual appearance of moving humans from occluded monocular videos is a challenging task. Most existing research renders 3D humans under ideal conditions, requiring a clear and unobstructed scene. Those methods cannot be used…

Computer Vision and Pattern Recognition · Computer Science 2025-08-18 Tiange Xiang , Adam Sun , Scott Delp , Kazuki Kozuka , Li Fei-Fei , Ehsan Adeli