Outputs (16)

Spoofing Detection on Hand Images Using Quality Assessment (2021)
Journal Article
Bera, A., Dey, R., Bhattacharjee, D., Nasipuri, M. *., & Shum, H. (2021). Spoofing Detection on Hand Images Using Quality Assessment. Multimedia Tools and Applications, 80(19), 28603-28626. https://doi.org/10.1007/s11042-021-10976-z

Recent research on biometrics focuses on achieving a high success rate of authentication and addressing the concern of various spoofing attacks. Although hand geometry recognition provides adequate security over unauthorized access, it is susceptible... Read More about Spoofing Detection on Hand Images Using Quality Assessment.

Stable Hand Pose Estimation under Tremor via Graph Neural Network (2021)
Conference Proceeding
Leng, Z., Chen, J., Shum, H. P., Li, F. W., & Liang, X. (2021). Stable Hand Pose Estimation under Tremor via Graph Neural Network. In 2021 IEEE Virtual Reality and 3D User Interfaces (VR) (226-234). https://doi.org/10.1109/vr50410.2021.00044

Hand pose estimation, which predicts the spatial location of hand joints, is a fundamental task in VR/AR applications. Although existing methods can recover hand pose competently, the tremor issue occurring in hand motion has not been completely solv... Read More about Stable Hand Pose Estimation under Tremor via Graph Neural Network.

Makeup Style Transfer on Low-quality Images with Weighted Multi-scale Attention (2021)
Conference Proceeding
Organisciak, D., Ho, E. S., & Shum, H. P. (2021). Makeup Style Transfer on Low-quality Images with Weighted Multi-scale Attention. . https://doi.org/10.1109/icpr48806.2021.9412604

Facial makeup style transfer is an extremely challenging sub-field of image-to-image-translation. Due to this difficulty, state-of-the-art results are mostly reliant on the Face Parsing Algorithm, which segments a face into parts in order to easily e... Read More about Makeup Style Transfer on Low-quality Images with Weighted Multi-scale Attention.

A Two-Stream Recurrent Network for Skeleton-based Human Interaction Recognition (2021)
Conference Proceeding
Men, Q., Hoy, E. S., Shum, H. P., & Leung, H. (2021). A Two-Stream Recurrent Network for Skeleton-based Human Interaction Recognition. . https://doi.org/10.1109/icpr48806.2021.9412538

This paper addresses the problem of recognizing human-human interaction from skeletal sequences. Existing methods are mainly designed to classify single human action. Many of them simply stack the movement features of two characters to deal with huma... Read More about A Two-Stream Recurrent Network for Skeleton-based Human Interaction Recognition.

3D car shape reconstruction from a contour sketch using GAN and lazy learning (2021)
Journal Article
Nozawa, N., Shum, H. P., Feng, Q., Ho, E. S., & Morishima, S. (2022). 3D car shape reconstruction from a contour sketch using GAN and lazy learning. Visual Computer, 38(4), 1317-1330. https://doi.org/10.1007/s00371-020-02024-y

3D car models are heavily used in computer games, visual effects, and even automotive designs. As a result, producing such models with minimal labour costs is increasingly more important. To tackle the challenge, we propose a novel system to reconstr... Read More about 3D car shape reconstruction from a contour sketch using GAN and lazy learning.

Two-stage human verification using HandCAPTCHA and anti-spoofed finger biometrics with feature selection (2021)
Journal Article
Bera, A., Bhattacharjee, D., & Shum, H. P. (2021). Two-stage human verification using HandCAPTCHA and anti-spoofed finger biometrics with feature selection. Expert Systems with Applications, 171, https://doi.org/10.1016/j.eswa.2021.114583

This paper presents a human verification scheme in two independent stages to overcome the vulnerabilities of attacks and to enhance security. At the first stage, a hand image-based CAPTCHA (HandCAPTCHA) is tested to avert automated bot-attacks on the... Read More about Two-stage human verification using HandCAPTCHA and anti-spoofed finger biometrics with feature selection.