2 citations · 2 across the 4 of their papers we have counts for
11 papers · 1 filter
Circular Quasiconformal Deturbulence: Geometry-Based Restoration from Multiple Turbulent Frames
Chu Chen, Han Zhang, Lok Ming Lui
Imaging through inhomogeneous media often results in severe distortions, posing significant challenges to downstream image-processing tasks. The lack of clean paired images makes s…
Quasi-Conformal Convolution : A Learnable Convolution for Deep Learning on Simply Connected Open Surfaces
Han Zhang, Tsz Lok Ip, Lok Ming Lui
Deep learning on non-Euclidean domains is important for analyzing complex geometric data that lacks common coordinate systems and familiar Euclidean properties. A central challenge…
Deformation-Invariant Neural Network and Its Applications in Distorted Image Restoration and Analysis
Han Zhang, Qiguang Chen, Lok Ming Lui
Images degraded by geometric distortions pose a significant challenge to imaging and computer vision tasks such as object recognition. Deep learning-based imaging models usually fa…
Harmonic Beltrami Signature Network: a Shape Prior Module in Deep Learning Framework
Chenran Lin, Lok Ming Lui
This paper presents the Harmonic Beltrami Signature Network (HBSN), a novel deep learning architecture for computing the Harmonic Beltrami Signature (HBS) from binary-like images.…
A Registration-Based Star-Shape Segmentation Model and Fast Algorithms
Daoping Zhang, Xue-Cheng Tai, Lok Ming Lui
Image segmentation plays a crucial role in extracting objects of interest and identifying their boundaries within an image. However, accurate segmentation becomes challenging when…
Enhancing Facial Classification and Recognition using 3D Facial Models and Deep Learning
Houting Li, Mengxuan Dong, Lok Ming Lui
Accurate analysis and classification of facial attributes are essential in various applications, from human-computer interaction to security systems. In this work, a novel approach…