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Modeling deformable objects - especially continuum materials - in a way that is physically plausible, generalizable, and data-efficient remains challenging across 3D vision, graphics, and robotic manipulation. Many existing methods…

Robotics · Computer Science 2026-01-27 Yunuo Chen , Yafei Hu , Lingfeng Sun , Tushar Kusnur , Laura Herlant , Chenfanfu Jiang

We present the first real-time system capable of tracking and reconstructing, individually, every visible object in a given scene, without any form of prior on the rigidness of the objects, texture existence, or object category. In contrast…

Robotics · Computer Science 2022-10-11 Haonan Chang , Abdeslam Boularias

In this paper, we propose a new approach to deformable image registration that captures sliding motions. The large deformation diffeomorphic metric mapping (LDDMM) registration method faces challenges in representing sliding motion since it…

Optimization and Control · Mathematics 2023-03-15 Lili Bao , Jiahao Lu , Shihui Ying , Stefan Sommer

As generative models become increasingly capable of producing high-fidelity visual content, the demand for efficient, interpretable, and editable image representations has grown substantially. Recent advances in 2D Gaussian Splatting (2DGS)…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Hao Wang , Ashish Bastola , Chaoyi Zhou , Wenhui Zhu , Xiwen Chen , Xuanzhao Dong , Siyu Huang , Abolfazl Razi

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

Current 4D Gaussian frameworks for dynamic scene reconstruction deliver impressive visual fidelity and rendering speed, however, the inherent trade-off between storage costs and the ability to characterize complex physical motions…

Graphics · Computer Science 2025-07-11 Wei Yao , Shuzhao Xie , Letian Li , Weixiang Zhang , Zhixin Lai , Shiqi Dai , Ke Zhang , Zhi Wang

We introduce the Deformable Gaussian Splats Large Reconstruction Model (DGS-LRM), the first feed-forward method predicting deformable 3D Gaussian splats from a monocular posed video of any dynamic scene. Feed-forward scene reconstruction…

Deformable objects often appear in unstructured configurations. Tracing deformable objects helps bringing them into extended states and facilitating the downstream manipulation tasks. Due to the requirements for object-specific modeling or…

Desktop organization remains challenging for service robots because of heterogeneous objects and diverse manipulation objectives, such as collection and stacking. In this article, a task-oriented framework is presented for organizing planar…

Robotics · Computer Science 2026-05-12 Yi Dong , Yangjun Liu , Jinjun Duan , Yang Li , Zhendong Dai

Scene change detection methods built on Gaussian splatting universally follow a render-then-compare paradigm: the pre-change scene is rendered into 2D and compared against post-change images via pixel or feature residuals. This change…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Chamuditha Jayanga Galappaththige , Jason Lai , Timothy Patten , Donald Dansereau , Niko Suenderhauf , Dimity Miller

Realistic dynamic garments on animated characters have many AR/VR applications. While authoring such dynamic garment geometry is still a challenging task, data-driven simulation provides an attractive alternative, especially if it can be…

Computer Vision and Pattern Recognition · Computer Science 2022-09-26 Meng Zhang , Duygu Ceylan , Niloy J. Mitra

Structured 3D representations such as keypoints and meshes offer compact, expressive descriptions of deformable objects, jointly capturing geometric and topological information useful for downstream tasks such as dynamics modeling and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Yeheng Zong , Yizhou Chen , Alexander Bowler , Chia-Tung Yang , Ram Vasudevan

Recent 4D Gaussian Splatting (4DGS) methods achieve impressive dynamic scene reconstruction but often rely on piecewise linear velocity approximations and short temporal windows. This disjointed modeling leads to severe temporal…

Computer Vision and Pattern Recognition · Computer Science 2026-04-02 Suwoong Yeom , Joonsik Nam , Seunggyu Choi , Lucas Yunkyu Lee , Sangmin Kim , Jaesik Park , Joonsoo Kim , Kugjin Yun , Kyeongbo Kong , Sukju Kang

Dynamic scene rendering and reconstruction play a crucial role in computer vision and augmented reality. Recent methods based on 3D Gaussian Splatting (3DGS), have enabled accurate modeling of dynamic urban scenes, but for urban scenes they…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Siddharth Tourani , Jayaram Reddy , Akash Kumbar , Satyajit Tourani , Nishant Goyal , Madhava Krishna , N. Dinesh Reddy , Muhammad Haris Khan

Accurately digitizing physical objects is central to many applications, including virtual/augmented reality, industrial design, and e-commerce. Prior research has demonstrated efficient and faithful reconstruction of objects' geometric…

Graphics · Computer Science 2024-06-26 Yunxiang Zhang , Xin Sun , Dengfeng Li , Xinge Yu , Qi Sun

Non-Rigid Structure-from-Motion (NRSfM) problem aims to recover 3D geometry of a deforming object from its 2D feature correspondences across multiple frames. Classical approaches to this problem assume a small number of feature points and,…

Computer Vision and Pattern Recognition · Computer Science 2020-06-17 Suryansh Kumar , Luc Van Gool , Carlos E. P. de Oliveira , Anoop Cherian , Yuchao Dai , Hongdong Li

A complete representation of 3D objects requires characterizing the space of deformations in an interpretable manner, from articulations of a single instance to changes in shape across categories. In this work, we improve on a prior…

Computer Vision and Pattern Recognition · Computer Science 2023-03-21 Tristan Aumentado-Armstrong , Stavros Tsogkas , Sven Dickinson , Allan Jepson

Retrieving the 3D kinematics of articulated objects from monocular video is a fundamental challenge in computer vision. Existing methods rely on complex video setups or cues such as long-term point tracking or wide-baseline matching, but…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Arslan Artykov , Tom Ravaud , Nicolás Violante-Grezzi , Vincent Lepetit

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

This paper considers the problem of modeling articulated objects captured in 2D videos to enable novel view synthesis, while also being easily editable, drivable, and re-posable. To tackle this challenging problem, we propose RigGS, a new…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Yuxin Yao , Zhi Deng , Junhui Hou