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Related papers: DyCrowd: Towards Dynamic Crowd Reconstruction from…

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Image-based multi-person reconstruction in wide-field large scenes is critical for crowd analysis and security alert. However, existing methods cannot deal with large scenes containing hundreds of people, which encounter the challenges of…

Computer Vision and Pattern Recognition · Computer Science 2023-04-04 Hao Wen , Jing Huang , Huili Cui , Haozhe Lin , YuKun Lai , Lu Fang , Kun Li

This is a technical report for the GigaCrowd challenge. Reconstructing 3D crowds from monocular images is a challenging problem due to mutual occlusions, server depth ambiguity, and complex spatial distribution. Since no large-scale 3D…

Computer Vision and Pattern Recognition · Computer Science 2023-10-11 Buzhen Huang , Jingyi Ju , Yangang Wang

Single-view 3D human reconstruction has garnered significant attention in recent years. Despite numerous advancements, prior research has concentrated on reconstructing 3D models from clear, close-up images of individual subjects, often…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Yizheng Song , Yiyu Zhuang , Qipeng Xu , Haixiang Wang , Jiahe Zhu , Jing Tian , Siyu Zhu , Hao Zhu

Accurately detecting and tracking pedestrians in 3D space is challenging due to large variations in rotations, poses and scales. The situation becomes even worse for dense crowds with severe occlusions. However, existing benchmarks either…

Computer Vision and Pattern Recognition · Computer Science 2022-04-05 Peishan Cong , Xinge Zhu , Feng Qiao , Yiming Ren , Xidong Peng , Yuenan Hou , Lan Xu , Ruigang Yang , Dinesh Manocha , Yuexin Ma

This paper focuses on spatially consistent hundreds of human pose and shape reconstruction from a single large-scene image with various human scales under arbitrary camera FoVs (Fields of View). Due to the small and highly varying 2D human…

Computer Vision and Pattern Recognition · Computer Science 2025-05-26 Jing Huang , Hao Wen , Tianyi Zhou , Haozhe Lin , Yu-kun Lai , Kun Li

Crowd simulation is a central topic in several fields including graphics. To achieve high-fidelity simulations, data has been increasingly relied upon for analysis and simulation guidance. However, the information in real-world data is…

Graphics · Computer Science 2020-04-30 Feixiang He , Yuanhang Xiang , Xi Zhao , He Wang

High-quality 4D reconstruction of human performance with complex interactions to various objects is essential in real-world scenarios, which enables numerous immersive VR/AR applications. However, recent advances still fail to provide…

Computer Vision and Pattern Recognition · Computer Science 2021-05-03 Zhuo Su , Lan Xu , Dawei Zhong , Zhong Li , Fan Deng , Shuxue Quan , Lu Fang

It is important to monitor and analyze crowd events for the sake of city safety. In an EDOF (extended depth of field) image with a crowded scene, the distribution of people is highly imbalanced. People far away from the camera look much…

Computer Vision and Pattern Recognition · Computer Science 2018-04-24 Mingliang Xu , Zhaoyang Ge , Xiaoheng Jiang , Gaoge Cui , Pei Lv , Bing Zhou , Changsheng Xu

We present an approach for 3D global human mesh recovery from monocular videos recorded with dynamic cameras. Our approach is robust to severe and long-term occlusions and tracks human bodies even when they go outside the camera's field of…

Computer Vision and Pattern Recognition · Computer Science 2022-03-31 Ye Yuan , Umar Iqbal , Pavlo Molchanov , Kris Kitani , Jan Kautz

Navigating through dense human crowds remains a significant challenge for mobile robots. A key issue is the freezing robot problem, where the robot struggles to find safe motions and becomes stuck within the crowd. To address this, we…

Robotics · Computer Science 2026-03-03 Yufei Zhu , Shih-Min Yang , Martin Magnusson , Allan Wang

Crowd trajectory prediction plays a crucial role in public safety and management, where it can help prevent disasters such as stampedes. Recent works address the problem by predicting individual trajectories and considering surrounding…

Artificial Intelligence · Computer Science 2026-03-20 Antonius Bima Murti Wijaya , Paul Henderson , Marwa Mahmoud

Due to the mutual occlusion, severe scale variation, and complex spatial distribution, the current multi-person mesh recovery methods cannot produce accurate absolute body poses and shapes in large-scale crowded scenes. To address the…

Computer Vision and Pattern Recognition · Computer Science 2023-08-31 Buzhen Huang , Jingyi Ju , Zhihao Li , Yangang Wang

We introduce a novel framework for reconstructing dynamic human-object interactions from monocular video that overcomes challenges associated with occlusions and temporal inconsistencies. Traditional 3D reconstruction methods typically…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Hyungjun Doh , Dong In Lee , Seunggeun Chi , Pin-Hao Huang , Kwonjoon Lee , Sangpil Kim , Karthik Ramani

Multi-person 3D reconstruction is pivotal for real-world interaction analysis, yet remains challenging due to severe occlusions and depth ambiguity. Current approaches typically rely on single-modality inputs, which inherently lack…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Minghao Sun , Chongyang Xu , Yitao Xie , Buzhen Huang , Kun Li

We present CrowdSplat, a novel approach that leverages 3D Gaussian Splatting for real-time, high-quality crowd rendering. Our method utilizes 3D Gaussian functions to represent animated human characters in diverse poses and outfits, which…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Xiaohan Sun , Yinghan Xu , John Dingliana , Carol O'Sullivan

Crowd counting aims to count the number of instantaneous people in a crowded space, and many promising solutions have been proposed for single image crowd counting. With the ubiquitous video capture devices in public safety field, how to…

Computer Vision and Pattern Recognition · Computer Science 2022-02-15 Xingjiao Wu , Baohan Xu , Yingbin Zheng , Hao Ye , Jing Yang , Liang He

We study video crowd counting, which is to estimate the number of objects (people in this paper) in all the frames of a video sequence. Previous work on crowd counting is mostly on still images. There has been little work on how to properly…

Computer Vision and Pattern Recognition · Computer Science 2021-04-30 Haoyue Bai , S. -H. Gary Chan

The interest in 3D dynamical tracking is growing in fields such as robotics, biology and fluid dynamics. Recently, a major source of progress in 3D tracking has been the study of collective behaviour in biological systems, where the…

Computer Vision and Pattern Recognition · Computer Science 2015-11-05 Andrea Cavagna , Chiara Creato , Lorenzo Del Castello , Stefania Melillo , Leonardo Parisi , Massimiliano Viale

Crowd counting problem that counts the number of people in an image has been extensively studied in recent years. In this paper, we introduce a new variant of crowd counting problem, namely "Categorized Crowd Counting", that counts the…

Computer Vision and Pattern Recognition · Computer Science 2019-12-13 Sarkar Snigdha Sarathi Das , Syed Md. Mukit Rashid , Mohammed Eunus Ali

Recent works on dynamic 3D neural field reconstruction assume the input from synchronized multi-view videos whose poses are known. The input constraints are often not satisfied in real-world setups, making the approach impractical. We show…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Changwoon Choi , Jeongjun Kim , Geonho Cha , Minkwan Kim , Dongyoon Wee , Young Min Kim
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