2 papers
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…