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Fully supervised human mesh recovery methods are data-hungry and have poor generalizability due to the limited availability and diversity of 3D-annotated benchmark datasets. Recent progress in self-supervised human mesh recovery has been…

Computer Vision and Pattern Recognition · Computer Science 2022-09-13 Xuan Gong , Meng Zheng , Benjamin Planche , Srikrishna Karanam , Terrence Chen , David Doermann , Ziyan Wu

We present a novel method for 3D surface reconstruction from multiple images where only a part of the object of interest is captured. Our approach builds on two recent developments: surface reconstruction using neural radiance fields for…

Computer Vision and Pattern Recognition · Computer Science 2023-12-11 Savva Ignatyev , Daniil Selikhanovych , Oleg Voynov , Yiqun Wang , Peter Wonka , Stamatios Lefkimmiatis , Evgeny Burnaev

Reconstruction of a continuous surface of two-dimensional manifold from its raw, discrete point cloud observation is a long-standing problem. The problem is technically ill-posed, and becomes more difficult considering that various sensing…

Computer Vision and Pattern Recognition · Computer Science 2022-05-06 Zhangjin Huang , Yuxin Wen , Zihao Wang , Jinjuan Ren , Kui Jia

Obtaining photorealistic reconstructions of objects from sparse views is inherently ambiguous and can only be achieved by learning suitable reconstruction priors. Earlier works on sparse rigid object reconstruction successfully learned such…

Computer Vision and Pattern Recognition · Computer Science 2022-11-09 Samarth Sinha , Roman Shapovalov , Jeremy Reizenstein , Ignacio Rocco , Natalia Neverova , Andrea Vedaldi , David Novotny

The task of reconstructing detailed 3D human body models from images is interesting but challenging in computer vision due to the high freedom of human bodies. In order to tackle the problem, we propose a coarse-to-fine method to…

Computer Vision and Pattern Recognition · Computer Science 2020-12-14 Zhongguo Li , Magnus Oskarsson , Anders Heyden

The key challenge in learning dense correspondences lies in the lack of ground-truth matches for real image pairs. While photometric consistency losses provide unsupervised alternatives, they struggle with large appearance changes, which…

Computer Vision and Pattern Recognition · Computer Science 2021-08-19 Prune Truong , Martin Danelljan , Fisher Yu , Luc Van Gool

We propose to utilize self-supervised techniques in the 2D domain for fine-grained 3D shape segmentation tasks. This is inspired by the observation that view-based surface representations are more effective at modeling high-resolution…

Computer Vision and Pattern Recognition · Computer Science 2022-08-19 Gopal Sharma , Kangxue Yin , Subhransu Maji , Evangelos Kalogerakis , Or Litany , Sanja Fidler

Most recent approaches to monocular 3D human pose estimation rely on Deep Learning. They typically involve regressing from an image to either 3D joint coordinates directly or 2D joint locations from which 3D coordinates are inferred. Both…

Computer Vision and Pattern Recognition · Computer Science 2017-04-11 Bugra Tekin , Pablo Márquez-Neila , Mathieu Salzmann , Pascal Fua

Reconstructing a dynamic scene from image inputs is a fundamental computer vision task with many downstream applications. Despite recent advancements, existing approaches still struggle to achieve high-quality reconstructions from unseen…

Computer Vision and Pattern Recognition · Computer Science 2025-03-03 Sara Oblak , Despoina Paschalidou , Sanja Fidler , Matan Atzmon

Current multi-modal models exhibit a notable misalignment with the human visual system when identifying objects that are visually assimilated into the background. Our observations reveal that these multi-modal models cannot distinguish…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Ruolin Shen , Xiaozhong Ji , Kai WU , Jiangning Zhang , Yijun He , HaiHua Yang , Xiaobin Hu , Xiaoyu Sun

Recent advances in 3D Gaussian Splatting (3DGS) have enabled high-quality, real-time novel-view synthesis from multi-view images. However, most existing methods assume the object is captured in a single, static pose, resulting in incomplete…

Computer Vision and Pattern Recognition · Computer Science 2025-10-20 Ting-Yu Yen , Yu-Sheng Chiu , Shih-Hsuan Hung , Peter Wonka , Hung-Kuo Chu

While recent feed-forward 3D reconstruction models accelerate 3D reconstruction by jointly inferring dense geometry and camera poses in a single pass, their reliance on dense attention imposes a quadratic complexity, creating a prohibitive…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Weining Ren , Xiao Tan , Kai Han

We propose Flash3D, a method for scene reconstruction and novel view synthesis from a single image which is both very generalisable and efficient. For generalisability, we start from a "foundation" model for monocular depth estimation and…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Stanislaw Szymanowicz , Eldar Insafutdinov , Chuanxia Zheng , Dylan Campbell , João F. Henriques , Christian Rupprecht , Andrea Vedaldi

Recent approaches to jointly reconstruct 3D humans and objects from a single RGB image represent 3D shapes with template-based or coarse models, which fail to capture details of loose clothing on human bodies. In this paper, we introduce a…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Ayushi Dutta , Marco Pesavento , Marco Volino , Adrian Hilton , Armin Mustafa

Multi-focus image fusion, a technique to generate an all-in-focus image from two or more partially-focused source images, can benefit many computer vision tasks. However, currently there is no large and realistic dataset to perform…

Computer Vision and Pattern Recognition · Computer Science 2020-08-31 Juncheng Zhang , Qingmin Liao , Shaojun Liu , Haoyu Ma , Wenming Yang , Jing-Hao Xue

Single-view clothed human reconstruction holds a central position in virtual reality applications, especially in contexts involving intricate human motions. It presents notable challenges in achieving realistic clothing deformation. Current…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Hongsheng Wang , Xiang Cai , Xi Sun , Jinhong Yue , Zhanyun Tang , Shengyu Zhang , Feng Lin , Fei Wu

Reconstructing high-quality point clouds from images remains challenging in computer vision. Existing generative-model-based approaches, particularly diffusion-model approaches that directly learn the posterior, may suffer from…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Seunghyeok Shin , Dabin Kim , Hongki Lim

With the increasing demands of applications in virtual reality such as 3D films, virtual Human-Machine Interactions and virtual agents, the analysis of 3D human face analysis is considered to be more and more important as a fundamental step…

Computer Vision and Pattern Recognition · Computer Science 2017-04-25 Shu Zhang , Hui Yu , Ting Wang , Junyu Dong , Honghai Liu

This paper introduces a novel multi-view 6 DoF object pose refinement approach focusing on improving methods trained on synthetic data. It is based on the DPOD detector, which produces dense 2D-3D correspondences between the model vertices…

Computer Vision and Pattern Recognition · Computer Science 2022-07-07 Ivan Shugurov , Ivan Pavlov , Sergey Zakharov , Slobodan Ilic

We present a dataset of 998 3D models of everyday tabletop objects along with their 847,000 real world RGB and depth images. Accurate annotations of camera poses and object poses for each image are performed in a semi-automated fashion to…

Computer Vision and Pattern Recognition · Computer Science 2022-08-10 Rakesh Shrestha , Siqi Hu , Minghao Gou , Ziyuan Liu , Ping Tan