Normal estimation for 3D point clouds is a fundamental task in 3D geometry processing. The state-of-the-art methods rely on priors of fitting local surfaces learned from normal supervision. However, ...

Learn how gradient descent really works by building it step by step in Python. No libraries, no shortcuts—just pure math and code made simple. Trump pulls US out of more than 30 UN bodies ICE shooting ...

Abstract: In this paper, we study asymptotic behaviors of continuous-time and discrete-time gradient flows of a “lower-unbounded” convex function on a Hadamard manifold, particularly, their ...

Abstract: This letter presents a novel finite- and fixed-time convergent framework for solving constrained convex optimization problems using safe gradient flow dynamics. In the existing literature, ...

Most existing point cloud upsampling methods have roughly three steps: feature extraction, feature expansion and 3D coordinate prediction. However, they usually suffer from two critical issues: (1) ...

The knowledge of hydraulic parameters in water distribution networks can indicate problems in real time, such as pipe bursts, small leakages, increase in pipe roughness and illegal connections.