Jiju Poovvancheri

Topological priors aren't just for features anymore: injecting persistent homology at multiple stages of point cloud networks—from sampling to regularization—boosts accuracy and robustness.

Forget hand-crafted topological features: this paper learns to select the *most* informative topological features for 3D shape analysis using a novel deep learning approach, boosting performance on standard tasks.