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We propose a novel method to accurately reconstruct a set of images representing a single scene from few linear multi-view measurements. Each observed image is modeled as the sum of a background image and a foreground one. The background…

Computer Vision and Pattern Recognition · Computer Science 2013-09-19 Gilles Puy , Pierre Vandergheynst

Trajectories are fundamental in different skiing disciplines. Tools enabling the analysis of such curves can enhance the training activity and enrich the broadcasting contents. However, the solutions currently available are based on…

Computer Vision and Pattern Recognition · Computer Science 2021-12-20 Matteo Dunnhofer , Alberto Zurini , Maurizio Dunnhofer , Christian Micheloni

Sports analysis requires processing large amounts of data, which is time-consuming and costly. Advancements in neural networks have significantly alleviated this burden, enabling highly accurate ball tracking in sports broadcasts. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Thomas Gossard , Andreas Ziegler , Andreas Zell

Creating high-quality articulated 3D models of animals is challenging either via manual creation or using 3D scanning tools. Therefore, techniques to reconstruct articulated 3D objects from 2D images are crucial and highly useful. In this…

Computer Vision and Pattern Recognition · Computer Science 2022-07-08 Chun-Han Yao , Wei-Chih Hung , Yuanzhen Li , Michael Rubinstein , Ming-Hsuan Yang , Varun Jampani

Object shape provides important information for robotic manipulation; for instance, selecting an effective grasp depends on both the global and local shape of the object of interest, while reaching into clutter requires accurate surface…

Robotics · Computer Science 2019-05-13 Kanrun Huang , Tucker Hermans

We address the problem of human motion tracking by registering a surface to 3-D data. We propose a method that iteratively computes two things: Maximum likelihood estimates for both the kinematic and free-motion parameters of a kinematic…

Computer Vision and Pattern Recognition · Computer Science 2023-11-21 Radu Horaud , Matti Niskanen , Guillaume Dewaele , Edmond Boyer

Motion segmentation in dynamic scenes is highly challenging, as conventional methods heavily rely on estimating camera poses and point correspondences from inherently noisy motion cues. Existing statistical inference or iterative…

Computer Vision and Pattern Recognition · Computer Science 2026-02-26 Xiankang He , Peile Lin , Ying Cui , Dongyan Guo , Chunhua Shen , Xiaoqin Zhang

We present a novel method for estimation of 3D human poses from a multi-camera setup, employing distributed smart edge sensors coupled with a backend through a semantic feedback loop. 2D joint detection for each camera view is performed…

Computer Vision and Pattern Recognition · Computer Science 2021-07-06 Simon Bultmann , Sven Behnke

Muscle-based systems have the potential to provide both anatomical accuracy and semantic interpretability as compared to blendshape models; however, a lack of expressivity and differentiability has limited their impact. Thus, we propose…

Computer Vision and Pattern Recognition · Computer Science 2018-12-10 Michael Bao , Matthew Cong , Stéphane Grabli , Ronald Fedkiw

Recent monocular 3D shape reconstruction methods have shown promising zero-shot results on object-segmented images without any occlusions. However, their effectiveness is significantly compromised in real-world conditions, due to imperfect…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Junhyeong Cho , Kim Youwang , Hunmin Yang , Tae-Hyun Oh

While the problem of estimating shapes and diffuse reflectances of human faces from images has been extensively studied, there is relatively less work done on recovering the specular albedo. This paper presents a lightweight solution for…

Computer Vision and Pattern Recognition · Computer Science 2019-11-28 Guoxian Song , Jianmin Zheng , Jianfei Cai , Tat-Jen Cham

Reconstructing dynamic scenes with large-scale and complex motions remains a significant challenge. Recent techniques like Neural Radiance Fields and 3D Gaussian Splatting (3DGS) have shown promise but still struggle with scenes involving…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Qiankun Gao , Yanmin Wu , Chengxiang Wen , Jiarui Meng , Luyang Tang , Jie Chen , Ronggang Wang , Jian Zhang

Reconstructing dynamic 3D scenes from 2D images and generating diverse views over time is challenging due to scene complexity and temporal dynamics. Despite advancements in neural implicit models, limitations persist: (i) Inadequate Scene…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 Zeyu Yang , Hongye Yang , Zijie Pan , Li Zhang

In this paper, we present a method to reconstruct the world and multiple dynamic humans in 3D from a monocular video input. As a key idea, we represent both the world and multiple humans via the recently emerging 3D Gaussian Splatting…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Inhee Lee , Byungjun Kim , Hanbyul Joo

This paper presents a novel framework to recover detailed human body shapes from a single image. It is a challenging task due to factors such as variations in human shapes, body poses, and viewpoints. Prior methods typically attempt to…

Computer Vision and Pattern Recognition · Computer Science 2019-05-14 Hao Zhu , Xinxin Zuo , Sen Wang , Xun Cao , Ruigang Yang

We present a novel framework that brings the 3D motion retargeting task from controlled environments to in-the-wild scenarios. In particular, our method is capable of retargeting body motion from a character in a 2D monocular video to a 3D…

Computer Vision and Pattern Recognition · Computer Science 2021-12-22 Wentao Zhu , Zhuoqian Yang , Ziang Di , Wayne Wu , Yizhou Wang , Chen Change Loy

This paper presents a comprehensive review on regression-based method for human pose estimation. The problem of human pose estimation has been intensively studied and enabled many application from entertainment to training. Traditional…

Computer Vision and Pattern Recognition · Computer Science 2017-09-08 Wenye He

We present a technique for a complete 3D reconstruction of small objects moving in front of a textured background. It is a particular variation of multibody structure from motion, which specializes to two objects only. The scene is captured…

Computer Vision and Pattern Recognition · Computer Science 2021-05-25 Petr Hruby , Tomas Pajdla

Robotics applications often rely on scene reconstructions to enable downstream tasks. In this work, we tackle the challenge of actively building an accurate map of an unknown scene using an RGB-D camera on a mobile platform. We propose a…

Robotics · Computer Science 2025-04-09 Liren Jin , Xingguang Zhong , Yue Pan , Jens Behley , Cyrill Stachniss , Marija Popović

We present the first method to capture the 3D total motion of a target person from a monocular view input. Given an image or a monocular video, our method reconstructs the motion from body, face, and fingers represented by a 3D deformable…

Computer Vision and Pattern Recognition · Computer Science 2018-12-05 Donglai Xiang , Hanbyul Joo , Yaser Sheikh