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Related papers: HuSc3D: Human Sculpture dataset for 3D object reco…

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We present UrbanScene3D, a large-scale data platform for research of urban scene perception and reconstruction. UrbanScene3D contains over 128k high-resolution images covering 16 scenes including large-scale real urban regions and synthetic…

Computer Vision and Pattern Recognition · Computer Science 2022-07-20 Liqiang Lin , Yilin Liu , Yue Hu , Xingguang Yan , Ke Xie , Hui Huang

Accurate 3D reconstruction of objects with reflective, transparent, or low-texture surfaces still remains notoriously challenging. Such materials often violate key assumptions in multi-view reconstruction pipelines, such as photometric…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Zhicheng Liang , Haoyi Yu , Boyan Li , Dayou Zhang , Zijian Cao , Tianyi Gong , Junhua Liu , Shuguang Cui , Fangxin Wang

Generating good quality and geometrically plausible synthetic images of humans with the ability to control appearance, pose and shape parameters, has become increasingly important for a variety of tasks ranging from photo editing, fashion…

Computer Vision and Pattern Recognition · Computer Science 2019-10-21 Mihai Zanfir , Elisabeta Oneata , Alin-Ionut Popa , Andrei Zanfir , Cristian Sminchisescu

We study 3D shape modeling from a single image and make contributions to it in three aspects. First, we present Pix3D, a large-scale benchmark of diverse image-shape pairs with pixel-level 2D-3D alignment. Pix3D has wide applications in…

Computer Vision and Pattern Recognition · Computer Science 2018-04-13 Xingyuan Sun , Jiajun Wu , Xiuming Zhang , Zhoutong Zhang , Chengkai Zhang , Tianfan Xue , Joshua B. Tenenbaum , William T. Freeman

In this paper, we present a large-scale detailed 3D face dataset, FaceScape, and the corresponding benchmark to evaluate single-view facial 3D reconstruction. By training on FaceScape data, a novel algorithm is proposed to predict elaborate…

Computer Vision and Pattern Recognition · Computer Science 2023-09-19 Hao Zhu , Haotian Yang , Longwei Guo , Yidi Zhang , Yanru Wang , Mingkai Huang , Menghua Wu , Qiu Shen , Ruigang Yang , Xun Cao

Reconstructing accurate 3D surfaces for street-view scenarios is crucial for applications such as digital entertainment and autonomous driving simulation. However, existing street-view datasets, including KITTI, Waymo, and nuScenes, only…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Yubin Hu , Kairui Wen , Heng Zhou , Xiaoyang Guo , Yong-Jin Liu

Asset management requires accurate 3D models to inform the maintenance, repair, and assessment of buildings, maritime vessels, and other key structures as they age. These downstream applications rely on high-fidelity models produced from…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 James L. Gray , Nikolai Goncharov , Alexandre Cardaillac , Ryan Griffiths , Jack Naylor , Donald G. Dansereau

Reconstructing texture-less surfaces poses unique challenges in computer vision, primarily due to the lack of specialized datasets that cater to the nuanced needs of depth and normals estimation in the absence of textural information. We…

Computer Vision and Pattern Recognition · Computer Science 2024-11-06 Muhammad Saif Ullah Khan , Sankalp Sinha , Didier Stricker , Marcus Liwicki , Muhammad Zeshan Afzal

This paper introduces a new real and synthetic dataset called NeRFBK specifically designed for testing and comparing NeRF-based 3D reconstruction algorithms. High-quality 3D reconstruction has significant potential in various fields, and…

Computer Vision and Pattern Recognition · Computer Science 2023-06-16 Ali Karami , Simone Rigon , Gabriele Mazzacca , Ziyang Yan , Fabio Remondino

3D dense reconstruction refers to the process of obtaining the complete shape and texture features of 3D objects from 2D planar images. 3D reconstruction is an important and extensively studied problem, but it is far from being solved. This…

Computer Vision and Pattern Recognition · Computer Science 2023-04-20 Yangming Li

For many fundamental scene understanding tasks, it is difficult or impossible to obtain per-pixel ground truth labels from real images. We address this challenge by introducing Hypersim, a photorealistic synthetic dataset for holistic…

Computer Vision and Pattern Recognition · Computer Science 2021-08-19 Mike Roberts , Jason Ramapuram , Anurag Ranjan , Atulit Kumar , Miguel Angel Bautista , Nathan Paczan , Russ Webb , Joshua M. Susskind

High-quality 3D human body reconstruction requires high-fidelity and large-scale training data and appropriate network design that effectively exploits the high-resolution input images. To tackle these problems, we propose a simple yet…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Sang-Hun Han , Min-Gyu Park , Ju Hong Yoon , Ju-Mi Kang , Young-Jae Park , Hae-Gon Jeon

While data has certainly taken the center stage in computer vision in recent years, it can still be difficult to obtain in certain scenarios. In particular, acquiring ground truth 3D shapes of objects pictured in 2D images remains a…

Computer Vision and Pattern Recognition · Computer Science 2016-08-02 Joao Carreira , Sara Vicente , Lourdes Agapito , Jorge Batista

Human head detection, keypoint estimation, and 3D head model fitting are essential tasks with many applications. However, traditional real-world datasets often suffer from bias, privacy, and ethical concerns, and they have been recorded in…

Computer Vision and Pattern Recognition · Computer Science 2024-12-06 Orest Kupyn , Eugene Khvedchenia , Christian Rupprecht

Reconstructing 3D objects is an important computer vision task that has wide application in AR/VR. Deep learning algorithm developed for this task usually relies on an unrealistic synthetic dataset, such as ShapeNet and Things3D. On the…

Computer Vision and Pattern Recognition · Computer Science 2022-06-27 Zhenpei Yang , Zaiwei Zhang , Qixing Huang

Despite the growing need for data of more and more sophisticated 3D reconstruction pipelines, we can still observe a scarcity of suitable public datasets. Existing 3D datasets are either low resolution, limited to a small amount of scenes,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Mattia D'Urso , Yuxi Hu , Christian Sormann , Mattia Rossi , Friedrich Fraundorfer

This paper investigates the evaluation of dense 3D face reconstruction from a single 2D image in the wild. To this end, we organise a competition that provides a new benchmark dataset that contains 2000 2D facial images of 135 subjects as…

Computer Vision and Pattern Recognition · Computer Science 2018-04-24 Zhen-Hua Feng , Patrik Huber , Josef Kittler , Peter JB Hancock , Xiao-Jun Wu , Qijun Zhao , Paul Koppen , Matthias Rätsch

Recently, there has been growing interest in developing learning-based methods to detect and utilize salient semi-global or global structures, such as junctions, lines, planes, cuboids, smooth surfaces, and all types of symmetries, for 3D…

Computer Vision and Pattern Recognition · Computer Science 2020-07-20 Jia Zheng , Junfei Zhang , Jing Li , Rui Tang , Shenghua Gao , Zihan Zhou

Digitizing the physical world into accurate simulation-ready virtual environments offers significant opportunities in a variety of fields such as augmented and virtual reality, gaming, and robotics. However, current 3D reconstruction and…

Computer Vision and Pattern Recognition · Computer Science 2025-10-08 Hongchi Xia , Chih-Hao Lin , Hao-Yu Hsu , Quentin Leboutet , Katelyn Gao , Michael Paulitsch , Benjamin Ummenhofer , Shenlong Wang

Recent advancements in radiance field rendering, exemplified by Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS), have significantly progressed 3D modeling and reconstruction. The use of multiple 360-degree omnidirectional…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Shintaro Ito , Natsuki Takama , Toshiki Watanabe , Koichi Ito , Hwann-Tzong Chen , Takafumi Aoki
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