GitHub

Few-shot Implicit Function Generation via Equivariance

Implicit Neural Representations (INRs) have emerged as a powerful framework for representing continuous signals. However, generating diverse INR weights remains challenging due to limited training ...
IEEE

Deep Implicit Moving Least-Squares Functions for 3D Reconstruction

Abstract: Point set is a flexible and lightweight representation widely used for 3D deep learning. However, their discrete nature prevents them from representing continuous and fine geometry, posing a ...
IEEE

I-Filtering: Implicit Filtering for Learning Neural Distance Functions from 3D Point Clouds

Abstract: Neural implicit functions including signed distance functions (SDFs) and unsigned distance functions (UDFs) have shown powerful ability in fitting the shape geometry. However, inferring ...
GitHub

Example code for integrating over the intersection of two implicit functions using the ...

I am currently working with the first method, which is the "Implicitly-defined domain specified by a single level set function, sufficiently-smooth but otherwise arbitrary". My requirement is to ...