My implementation and comparison of different learnable positional encoding strategies for transformer-based models. I built this to explore how different position encoding methods affect model ...

This repository contains the implementation of HOPE-WavePE (High-Order Permutation-Equivariant Autoencoder for Wavelet Positional Encoding), a novel graph representation learning method. HOPE-WavePE ...

Neural Radiance Fields (NeRF) have revolutionized novel view synthesis through volumetric scene representations, where positional encoding plays a critical role in high-frequency detail capture.

Abstract: Estimating the 6-DoF posture of parts in assembly-based modeling is a critical task in the fields of computer graphics, computer vision and robotics. A typical scenario involves enabling a ...

Positional encoding has become the de facto standard for grounding deep neural networks on discrete point-wise positions, and it has achieved remarkable success in tasks where the input can be ...