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Dynamic scene reconstruction is a long-term challenge in the field of 3D vision. Recently, the emergence of 3D Gaussian Splatting has provided new insights into this problem. Although subsequent efforts rapidly extend static 3D Gaussian to…

Computer Vision and Pattern Recognition · Computer Science 2024-10-11 Ruijie Zhu , Yanzhe Liang , Hanzhi Chang , Jiacheng Deng , Jiahao Lu , Wenfei Yang , Tianzhu Zhang , Yongdong Zhang

Recent advancements in 3D scene editing have been propelled by the rapid development of generative models. Existing methods typically utilize generative models to perform text-guided editing on 3D representations, such as 3D Gaussian…

Graphics · Computer Science 2025-05-27 Yansong Qu , Dian Chen , Xinyang Li , Xiaofan Li , Shengchuan Zhang , Liujuan Cao , Rongrong Ji

Applications in virtual and augmented reality create a demand for rapid creation and easy access to large sets of 3D models. An effective way to address this demand is to edit or deform existing 3D models based on a reference, e.g., a 2D…

Computer Vision and Pattern Recognition · Computer Science 2019-03-11 Weiyue Wang , Duygu Ceylan , Radomir Mech , Ulrich Neumann

In a computer-based virtual environment, objects may collide with each other. Therefore, different algorithms are needed to detect the collision and perform a correct action in order to avoid penetration. Based on the application and…

Computational Geometry · Computer Science 2017-09-18 Ehsan Arbabi

High-fidelity 3D video reconstruction is essential for enabling real-time rendering of dynamic scenes with realistic motion in virtual and augmented reality (VR/AR). The deformation field paradigm of 3D Gaussian splatting has achieved…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 Zhenyang Li , Xiaoyang Bai , Tongchen Zhang , Pengfei Shen , Weiwei Xu , Yifan Peng

We present a method for nonrigid registration of 2-D geometric shapes. Our contribution is twofold. First, we extend the classic chamfer-matching energy to a variational functional. Secondly, we introduce a meshless deformation model that…

Computer Vision and Pattern Recognition · Computer Science 2011-04-22 Wei Liu , Eraldo Ribeiro

Taking an image of an object is at its core a lossy process. The rich information about the three-dimensional structure of the world is flattened to an image plane and decisions such as viewpoint and camera parameters are final and not…

Computer Vision and Pattern Recognition · Computer Science 2016-08-16 Konstantinos Rematas , Chuong Nguyen , Tobias Ritschel , Mario Fritz , Tinne Tuytelaars

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…

If robots could reliably manipulate the shape of 3D deformable objects, they could find applications in fields ranging from home care to warehouse fulfillment to surgical assistance. Analytic models of elastic, 3D deformable objects require…

Robotics · Computer Science 2022-04-20 Bao Thach , Brian Y. Cho , Alan Kuntz , Tucker Hermans

Language-driven 3D Gaussian Splatting (3DGS) editing provides a more convenient approach for modifying complex scenes in VR/AR. Standard pipelines typically adopt a two-stage strategy: first editing multiple 2D views, and then optimizing…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Yanhui Chen , Jiahong Li , Jingchao Wang , Junyi Lin , Zixin Zeng , Yang Shi

At the classical level, redefinitions of the field content of a Lagrangian allow to rewrite an interacting model on a flat target space, in the form of a free field model (no potential term) on a curved target space. In the present work we…

High Energy Physics - Theory · Physics 2015-09-03 Victor I. Afonso , Diego J. Cirilo-Lombardo

Neural shape models can represent complex 3D shapes with a compact latent space. When applied to dynamically deforming shapes such as the human hands, however, they would need to preserve temporal coherence of the deformation as well as the…

Computer Vision and Pattern Recognition · Computer Science 2021-10-06 Binbin Xu , Lingni Ma , Yuting Ye , Tanner Schmidt , Christopher D. Twigg , Steven Lovegrove

Recent advances in 3D Gaussian Splatting (3D-GS) have shown remarkable success in representing 3D scenes and generating high-quality, novel views in real-time. However, 3D-GS and its variants assume that input images are captured based on…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Liao Shen , Tianqi Liu , Huiqiang Sun , Jiaqi Li , Zhiguo Cao , Wei Li , Chen Change Loy

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

In this work, we introduce Coca-Splat, a novel approach to addressing the challenges of sparse view pose-free scene reconstruction and novel view synthesis (NVS) by jointly optimizing camera parameters with 3D Gaussians. Inspired by…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Jiamin Wu , Hongyang Li , Xiaoke Jiang , Yuan Yao , Lei Zhang

Reconstructing 3D geometry and appearance from a sparse set of fixed cameras is a foundational task with broad applications, yet it remains fundamentally constrained by the limited viewpoints. We show that this bound can be broken by…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Ryosuke Hirai , Kohei Yamashita , Antoine Guédon , Ryo Kawahara , Vincent Lepetit , Ko Nishino

Recently, deep-learning-based approaches have been widely studied for deformable image registration task. However, most efforts directly map the composite image representation to spatial transformation through the convolutional neural…

Image and Video Processing · Electrical Eng. & Systems 2022-07-08 Jiashun Chen , Donghuan Lu , Yu Zhang , Dong Wei , Munan Ning , Xinyu Shi , Zhe Xu , Yefeng Zheng

We present a technique for automatically producing a deformation of an input triangle mesh, guided solely by a text prompt. Our framework is capable of deformations that produce both large, low-frequency shape changes, and small…

Computer Vision and Pattern Recognition · Computer Science 2023-04-27 William Gao , Noam Aigerman , Thibault Groueix , Vladimir G. Kim , Rana Hanocka

We present GSD, a diffusion model approach based on Gaussian Splatting (GS) representation for 3D object reconstruction from a single view. Prior works suffer from inconsistent 3D geometry or mediocre rendering quality due to improper…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Yuxuan Mu , Xinxin Zuo , Chuan Guo , Yilin Wang , Juwei Lu , Xiaofeng Wu , Songcen Xu , Peng Dai , Youliang Yan , Li Cheng

In this paper, we analyze the viewpoint stability of foundational models - specifically, their sensitivity to changes in viewpoint- and define instability as significant feature variations resulting from minor changes in viewing angle,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Mateusz Michalkiewicz , Sheena Bai , Mahsa Baktashmotlagh , Varun Jampani , Guha Balakrishnan
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