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Due to inevitable noises introduced during scanning and quantization, 3D reconstruction via RGB-D sensors suffers from errors both in geometry and texture, leading to artifacts such as camera drifting, mesh distortion, texture ghosting, and…

Computer Vision and Pattern Recognition · Computer Science 2022-09-13 Jingbo Zhang , Ziyu Wan , Jing Liao

Reconstructing 3D objects from a single image is an intriguing but challenging problem. One promising solution is to utilize multi-view (MV) 3D reconstruction to fuse generated MV images into consistent 3D objects. However, the generated…

Computer Vision and Pattern Recognition · Computer Science 2024-01-30 Yizheng Chen , Rengan Xie , Qi Ye , Sen Yang , Zixuan Xie , Tianxiao Chen , Rong Li , Yuchi Huo

Nowadays, it is possible to scan faces and automatically register them with high quality. However, the resulting face meshes often need further processing: we need to stabilize them to remove unwanted head movement. Stabilization is…

Computer Vision and Pattern Recognition · Computer Science 2024-11-25 Jan Bednarik , Erroll Wood , Vasileios Choutas , Timo Bolkart , Daoye Wang , Chenglei Wu , Thabo Beeler

We present a Gaussian Splatting method for surface reconstruction using sparse input views. Previous methods relying on dense views struggle with extremely sparse Structure-from-Motion points for initialization. While learning-based…

Computer Vision and Pattern Recognition · Computer Science 2025-04-30 Jiang Wu , Rui Li , Yu Zhu , Rong Guo , Jinqiu Sun , Yanning Zhang

We propose a robust and accurate non-parametric method for single-view 3D face reconstruction (SVFR). While tremendous efforts have been devoted to parametric SVFR, a visible gap still lies between the result 3D shape and the ground truth.…

Computer Vision and Pattern Recognition · Computer Science 2023-02-14 Longwei Guo , Hao Zhu , Yuanxun Lu , Menghua Wu , Xun Cao

"Frontalization" is the process of synthesizing frontal facing views of faces appearing in single unconstrained photos. Recent reports have suggested that this process may substantially boost the performance of face recognition systems.…

Computer Vision and Pattern Recognition · Computer Science 2014-12-01 Tal Hassner , Shai Harel , Eran Paz , Roee Enbar

Recently, regression-based methods have dominated the field of 3D human pose and shape estimation. Despite their promising results, a common issue is the misalignment between predictions and image observations, often caused by minor joint…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Tom Wehrbein , Bodo Rosenhahn , Iain Matthews , Carsten Stoll

While existing methods for 3D face reconstruction from in-the-wild images excel at recovering the overall face shape, they commonly miss subtle, extreme, asymmetric, or rarely observed expressions. We improve upon these methods with SMIRK…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 George Retsinas , Panagiotis P. Filntisis , Radek Danecek , Victoria F. Abrevaya , Anastasios Roussos , Timo Bolkart , Petros Maragos

3D face reconstruction and face alignment are two fundamental and highly related topics in computer vision. Recently, some works start to use deep learning models to estimate the 3DMM coefficients to reconstruct 3D face geometry. However,…

Computer Vision and Pattern Recognition · Computer Science 2021-03-30 Zihao Jian , Minshan Xie

Learning a dense 3D model with fine-scale details from a single facial image is highly challenging and ill-posed. To address this problem, many approaches fit smooth geometries through facial prior while learning details as additional…

Computer Vision and Pattern Recognition · Computer Science 2022-03-21 Xingyu Ren , Alexandros Lattas , Baris Gecer , Jiankang Deng , Chao Ma , Xiaokang Yang , Stefanos Zafeiriou

We present a novel face reconstruction method capable of reconstructing detailed face geometry, spatially varying face reflectance from a single monocular image. We build our work upon the recent advances of DNN-based auto-encoders with…

Computer Vision and Pattern Recognition · Computer Science 2022-04-06 Abdallah Dib , Junghyun Ahn , Cedric Thebault , Philippe-Henri Gosselin , Louis Chevallier

In this paper, we propose a novel method for joint recovery of camera pose, object geometry and spatially-varying Bidirectional Reflectance Distribution Function (svBRDF) of 3D scenes that exceed object-scale and hence cannot be captured…

Computer Vision and Pattern Recognition · Computer Science 2023-06-07 Carolin Schmitt , Božidar Antić , Andrei Neculai , Joo Ho Lee , Andreas Geiger

Recently, a lot of attention has been focused on the incorporation of 3D data into face analysis and its applications. Despite providing a more accurate representation of the face, 3D facial images are more complex to acquire than 2D…

Computer Vision and Pattern Recognition · Computer Science 2021-03-01 Araceli Morales , Gemma Piella , Federico M. Sukno

In this work, we use multi-view aerial images to reconstruct the geometry, lighting, and material of facades using neural signed distance fields (SDFs). Without the requirement of complex equipment, our method only takes simple RGB images…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Zixuan Xie , Rengan Xie , Rong Li , Kai Huang , Pengju Qiao , Jingsen Zhu , Xu Yin , Qi Ye , Wei Hua , Yuchi Huo , Hujun Bao

Depth acquisition, based on active illumination, is essential for autonomous and robotic navigation. LiDARs (Light Detection And Ranging) with mechanical, fixed, sampling templates are commonly used in today's autonomous vehicles. An…

Computer Vision and Pattern Recognition · Computer Science 2019-08-06 Adam Wolff , Shachar Praisler , Ilya Tcenov , Guy Gilboa

3D-controllable portrait synthesis has significantly advanced, thanks to breakthroughs in generative adversarial networks (GANs). However, it is still challenging to manipulate existing face images with precise 3D control. While…

Computer Vision and Pattern Recognition · Computer Science 2022-08-25 Yuchen Liu , Zhixin Shu , Yijun Li , Zhe Lin , Richard Zhang , S. Y. Kung

3D Morphable Models (3DMMs) demonstrate great potential for reconstructing faithful and animatable 3D facial surfaces from a single image. The facial surface is influenced by the coarse shape, as well as the static detail (e,g.,…

Computer Vision and Pattern Recognition · Computer Science 2023-08-24 Zenghao Chai , Tianke Zhang , Tianyu He , Xu Tan , Tadas Baltrušaitis , HsiangTao Wu , Runnan Li , Sheng Zhao , Chun Yuan , Jiang Bian

Recent advances in optimizing Gaussian Splatting for scene geometry have enabled efficient reconstruction of detailed surfaces from images. However, when input views are sparse, such optimization is prone to overfitting, leading to…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Meiying Gu , Jiawei Zhang , Jiahe Li , Xiaohan Yu , Haonan Luo , Jin Zheng , Xiao Bai

Facial geometry and appearance capture have demonstrated tremendous success in 3D scanning real humans in studios. Recent works propose to democratize this technique while keeping the results high quality. However, they are still…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Yuxuan Han , Junfeng Lyu , Feng Xu

Accurate 3D reconstruction from multi-view images is essential for downstream robotic tasks such as navigation, manipulation, and environment understanding. However, obtaining precise camera poses in real-world settings remains challenging,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-12 Sriram Srinivasan , Gautam Ramachandra