most citedDeformation-Invariant Neural Network and Its Applications in Distorted Image Restoration and Analysis

2 citations · 2 across the 5 of their papers we have counts for

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cs.CV2026

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…

cs.CV2026

Learning Task-Aware Sampling with Shared Saliency through Density-Equalizing Mappings

Tsz Lok Ip, Han Zhang, Lok Ming Lui

In image and surface-based learning tasks, convolutional features are typically extracted using receptive fields that are sampled uniformly across the entire domain. However, infor…

cs.CV2026

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…

cs.CV20262 cited

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…

cs.CV2024

QIS : Interactive Segmentation via Quasi-Conformal Mappings

Han Zhang, Daoping Zhang, Lok Ming Lui

Image segmentation plays a crucial role in extracting important objects of interest from images, enabling various applications. While existing methods have shown success in segment…