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Reconstructing people, objects, and their interactions in 3D is a long-standing goal for intelligent systems. Often the input is RGB video from a moving camera, making the task ill-posed; depth is ambiguous, humans and objects occlude each…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Lixin Xue , Chengwei Zheng , Georgios Paschalidis , Chen Guo , Manuel Kaufmann , Juan Zarate , Dimitrios Tzionas

We propose GSO-SLAM, a real-time monocular dense SLAM system that leverages Gaussian scene representation. Unlike existing methods that couple tracking and mapping with a unified scene, incurring computational costs, or loosely integrate…

Computer Vision and Pattern Recognition · Computer Science 2026-02-13 Jiung Yeon , Seongbo Ha , Hyeonwoo Yu

Online monocular 3D reconstruction enables dense scene recovery from streaming video but remains fundamentally limited by the stability-adaptation dilemma: the reconstruction model must rapidly incorporate novel viewpoints while preserving…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Lanbo Xu , Liang Guo , Caigui Jiang , Cheng Wang

Point tracking aims to localize corresponding points across video frames, serving as a fundamental task for 4D reconstruction, robotics, and video editing. Existing methods commonly rely on shallow convolutional backbones such as ResNet…

Computer Vision and Pattern Recognition · Computer Science 2025-12-24 Soowon Son , Honggyu An , Chaehyun Kim , Hyunah Ko , Jisu Nam , Dahyun Chung , Siyoon Jin , Jung Yi , Jaewon Min , Junhwa Hur , Seungryong Kim

Recent studies on motion estimation have advocated an optimized motion representation that is globally consistent across the entire video, preferably for every pixel. This is challenging as a uniform representation may not account for the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Rui Li , Dong Liu

Building high-fidelity digital twins of articulated objects from visual data remains a central challenge. Existing approaches depend on multi-view captures of the object in discrete, static states, which severely constrains their real-world…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Lijun Guo , Haoyu Zhao , Xingyue Zhao , Rong Fu , Linghao Zhuang , Siteng Huang , Zhongyu Li , Hua Zou

3D dynamic point clouds provide a discrete representation of real-world objects or scenes in motion, which have been widely applied in immersive telepresence, autonomous driving, surveillance, etc. However, point clouds acquired from…

Computer Vision and Pattern Recognition · Computer Science 2022-04-20 Qianjiang Hu , Wei Hu

Multi-view video reconstruction plays a vital role in computer vision, enabling applications in film production, virtual reality, and motion analysis. While recent advances such as 4D Gaussian Splatting (4DGS) have demonstrated impressive…

Computer Vision and Pattern Recognition · Computer Science 2025-11-17 Zhixin Xu , Hengyu Zhou , Yuan Liu , Wenhan Xue , Hao Pan , Wenping Wang , Bin Wang

Recent advances in 4D scene reconstruction have significantly improved dynamic modeling across various domains. However, existing approaches remain limited under aerial conditions with single-view capture, wide spatial range, and dynamic…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Hanyang Liu , Rongjun Qin

We present MonoPSR, a monocular 3D object detection method that leverages proposals and shape reconstruction. First, using the fundamental relations of a pinhole camera model, detections from a mature 2D object detector are used to generate…

Computer Vision and Pattern Recognition · Computer Science 2019-04-04 Jason Ku , Alex D. Pon , Steven L. Waslander

Recovering temporally consistent 3D human body pose, shape and motion from a monocular video is a challenging task due to (self-)occlusions, poor lighting conditions, complex articulated body poses, depth ambiguity, and limited availability…

Computer Vision and Pattern Recognition · Computer Science 2023-11-21 Sushovan Chanda , Amogh Tiwari , Lokender Tiwari , Brojeshwar Bhowmick , Avinash Sharma , Hrishav Barua

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

Dynamic scene reconstruction from casual videos has seen recent remarkable progress. Numerous approaches have attempted to overcome the ill-posedness of the task by distilling priors from 2D foundational models and by imposing hand-crafted…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Narek Tumanyan , Samuel Rota Bulò , Denis Rozumny , Lorenzo Porzi , Adam Harley , Tali Dekel , Peter Kontschieder , Jonathon Luiten

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

Capturing general deforming scenes from monocular RGB video is crucial for many computer graphics and vision applications. However, current approaches suffer from drawbacks such as struggling with large scene deformations, inaccurate shape…

Computer Vision and Pattern Recognition · Computer Science 2023-05-05 Erik C. M. Johnson , Marc Habermann , Soshi Shimada , Vladislav Golyanik , Christian Theobalt

We propose a 3D multi-object tracking (MOT) solution using only 2D detections from monocular cameras, which automatically initiates/terminates tracks as well as resolves track appearance-reappearance and occlusions. Moreover, this approach…

Computer Vision and Pattern Recognition · Computer Science 2024-05-30 Linh Van Ma , Tran Thien Dat Nguyen , Ba-Ngu Vo , Hyunsung Jang , Moongu Jeon

We introduce a novel camera model for monocular 3D Morphable Model (3DMM) regression methods that effectively captures the perspective distortion effect commonly seen in close-up facial images. Fitting 3D morphable models to video is a key…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Toby Chong , Ryota Nakajima

Deformable 3D Gaussian Splatting (3D-GS) is limited by missing intermediate motion information due to the low temporal resolution of RGB cameras. To address this, we introduce the first approach combining event cameras, which capture…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Wenhao Xu , Wenming Weng , Yueyi Zhang , Ruikang Xu , Zhiwei Xiong

Reconstructing urban scenes is challenging due to their complex geometries and the presence of potentially dynamic objects. 3D Gaussian Splatting (3DGS)-based methods have shown strong performance, but existing approaches often incorporate…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Ziwen Li , Jiaxin Huang , Runnan Chen , Yunlong Che , Yandong Guo , Tongliang Liu , Fakhri Karray , Mingming Gong

Existing methods for reconstructing objects and humans from a monocular image suffer from severe mesh collisions and performance limitations for interacting occluding objects. This paper introduces a method to obtain a globally consistent…

Computer Vision and Pattern Recognition · Computer Science 2024-08-16 Sarthak Batra , Partha P. Chakrabarti , Simon Hadfield , Armin Mustafa