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Also recently, exciting strides forward have been made in the area of image restoration, particularly for image denoising and single image super-resolution. Deep learning techniques contributed to this significantly. The top methods differ…

Computer Vision and Pattern Recognition · Computer Science 2016-07-27 Jiqing Wu , Radu Timofte , Luc Van Gool

Reshaping accurate and realistic 3D human bodies from anthropometric parameters (e.g., height, chest size, etc.) poses a fundamental challenge for person identification, online shopping and virtual reality. Existing approaches for creating…

Computer Vision and Pattern Recognition · Computer Science 2021-04-06 Yanhong Zeng , Jianlong Fu , Hongyang Chao

Texture reconstruction techniques generally suffer from the errors in keyframe poses. We present a non-iterative method for seamless texture reconstruction of a given 3D scene. Our method finds the best texture alignment in a single shot…

Computer Vision and Pattern Recognition · Computer Science 2020-11-03 Mohammad Rouhani , Matthieu Fradet , Caroline Baillard

Most 3D face reconstruction methods rely on 3D morphable models, which disentangle the space of facial deformations into identity geometry, expressions and skin reflectance. These models are typically learned from a limited number of 3D…

Computer Vision and Pattern Recognition · Computer Science 2020-10-06 Mallikarjun B R , Ayush Tewari , Hans-Peter Seidel , Mohamed Elgharib , Christian Theobalt

3D reconstruction of endoscopic surgery scenes plays a vital role in enhancing scene perception, enabling AR visualization, and supporting context-aware decision-making in image-guided surgery. A critical yet challenging step in this…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Changhao Zhang , Matthew J. Clarkson , Mobarak I. Hoque

Existing methods of 3D dense face alignment mainly concentrate on accuracy, thus limiting the scope of their practical applications. In this paper, we propose a novel regression framework named 3DDFA-V2 which makes a balance among speed,…

Computer Vision and Pattern Recognition · Computer Science 2021-02-09 Jianzhu Guo , Xiangyu Zhu , Yang Yang , Fan Yang , Zhen Lei , Stan Z. Li

Cascaded regression has been recently applied to reconstructing 3D faces from single 2D images directly in shape space, and achieved state-of-the-art performance. This paper investigates thoroughly such cascaded regression based 3D face…

Computer Vision and Pattern Recognition · Computer Science 2017-04-19 Feng Liu , Dan Zeng , Jing Li , Qijun Zhao

Image retrieval is a fundamental task in computer vision. Despite recent advances in this field, many techniques have been evaluated on a limited number of domains, with a small number of instance categories. Notably, most existing works…

Computer Vision and Pattern Recognition · Computer Science 2023-09-29 Pengxiang Wu , Siman Wang , Kevin Dela Rosa , Derek Hao Hu

Accurate, reproducible burn assessment is critical for treatment planning, healing monitoring, and medico-legal documentation, yet conventional visual inspection and 2D photography are subjective and limited for longitudinal comparison.…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 S. Kalaycioglu , C. Hong , K. Zhai , H. Xie , J. N. Wong

Previous evaluations on 6DoF object pose tracking have presented obvious limitations along with the development of this area. In particular, the evaluation protocols are not unified for different methods, the widely-used YCBV dataset…

Computer Vision and Pattern Recognition · Computer Science 2023-09-18 Yang Li , Fan Zhong , Xin Wang , Shuangbing Song , Jiachen Li , Xueying Qin , Changhe Tu

The 3D mesh is an important representation of geometric data. In the generation of mesh data, geometric deficiencies (e.g., duplicate elements, degenerate faces, isolated vertices, self-intersection, and inner faces) are unavoidable and may…

Computer Vision and Pattern Recognition · Computer Science 2020-09-04 Bingtao Ma , Hongsen Liu , Liangliang Nan , Yang Cong

Real-time, high-quality, 3D scanning of large-scale scenes is key to mixed reality and robotic applications. However, scalability brings challenges of drift in pose estimation, introducing significant errors in the accumulated model.…

Graphics · Computer Science 2017-02-09 Angela Dai , Matthias Nießner , Michael Zollhöfer , Shahram Izadi , Christian Theobalt

Recovering 3D object pose and shape from a single image is a challenging and ill-posed problem. This is due to strong (self-)occlusions, depth ambiguities, the vast intra- and inter-class shape variance, and the lack of 3D ground truth for…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 Dimitrije Antić , Georgios Paschalidis , Shashank Tripathi , Theo Gevers , Sai Kumar Dwivedi , Dimitrios Tzionas

Recent 3D face reconstruction methods have made remarkable advancements, yet there remain huge challenges in monocular high-quality facial reflectance reconstruction. Existing methods rely on a large amount of light-stage captured data to…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Xingyu Ren , Jiankang Deng , Yuhao Cheng , Jia Guo , Chao Ma , Yichao Yan , Wenhan Zhu , Xiaokang Yang

3D face reconstruction from a single 2D image is a very important topic in computer vision. However, the current reconstruction methods are usually non-sensitive to face identities and over-sensitive to facial poses, which may result in…

Computer Vision and Pattern Recognition · Computer Science 2019-05-17 Yao Luo , Xiaoguang Tu , Mei Xie

One-shot face re-enactment is a challenging task due to the identity mismatch between source and driving faces. Specifically, the suboptimally disentangled identity information of driving subjects would inevitably interfere with the…

Computer Vision and Pattern Recognition · Computer Science 2022-11-24 Yunfan Liu , Qi Li , Zhenan Sun , Tieniu Tan

Depth estimation is a fundamental task in computer vision with diverse applications. Recent advancements in deep learning have led to powerful depth foundation models (DFMs), yet their evaluation remains challenging due to inconsistencies…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Zhenyu Li , Haotong Lin , Jiashi Feng , Peter Wonka , Bingyi Kang

Digital fringe projection (DFP) enables micrometer-level 3D reconstruction, yet extending it to large-scale mapping remains challenging because six-degree-of-freedom pose estimation often cannot match the reconstruction's precision.…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Sehoon Tak , Keunhee Cho , Sangpil Kim , Jae-Sang Hyun

Evaluating the performance of Multi-modal Large Language Models (MLLMs), integrating both point cloud and language, presents significant challenges. The lack of a comprehensive assessment hampers determining whether these models truly…

Computer Vision and Pattern Recognition · Computer Science 2024-04-24 Junjie Zhang , Tianci Hu , Xiaoshui Huang , Yongshun Gong , Dan Zeng

In this work, we present a new method for 3D face reconstruction from sparse-view RGB images. Unlike previous methods which are built upon 3D morphable models (3DMMs) with limited details, we leverage an implicit representation to encode…

Computer Vision and Pattern Recognition · Computer Science 2022-10-04 Moran Li , Haibin Huang , Yi Zheng , Mengtian Li , Nong Sang , Chongyang Ma
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