This repo contains the work done for CMSC 828I.It showcases a basic concept of a Implicit Neural Representation for a Single Image
-
Updated
Dec 21, 2023 - Jupyter Notebook
This repo contains the work done for CMSC 828I.It showcases a basic concept of a Implicit Neural Representation for a Single Image
Repository containing code for Siamese SIREN: Audio Compression with Implicit Neural Representations. Published as a workshop paper at ICML 2023 neural compression workshop.
SAD-SLAM: Sign-Agnostic Dynamic Simultaneous Localization and Mapping
Pytorch3d rendering an visualization basics
An implicit neural representation framework to correct motion artifacts from CT. Author: Zhennong Chen, PhD
This repository, contains my academic work for the Fall 2023 CMSC828I course. It includes assignments, projects, and relevant documentation covering various aspects of computer vision and recognition.
Official Code for "Representing Anatomical Trees by Denoising Diffusion of Implicit Neural Fields"
Machine Learning Framework with Automatic Differentiation and Cuda Acceleration in C++
Official implementation of DEQ-MPI: A deep equilibrium reconstruction model for magnetic particle imaging
[ICCV 2023] Curvature-Aware Training for Coordinate Networks
Representing Anatomical Trees by Denoising Diffusion of Implicit Neural Fields
Pytorch based unofficial implementation of "Multiplicative Filter Networks" paper by Fathony, Sahu, Willmott, & Kolter at ICLR 2021.
Implementation of two phase field approaches for the surface reconstruction problem and shape space learning. One based of the Modica-Mortola theorem and the other based on Ambrosio-Tortorelli
With INR, we parameterize some signal (in our case images) with a neural network (in this assignment, we will use a basic feed-forward network).
A PyTorch implementation of "DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation" by Park et al
FENRI (Fiber Orientations from Explicit Neural Representations) Implementation Repository
End-to-End Framework for Continuous Space-Time Super-Resolution on Remote Sensing data.
[ECCV'22] "Few 'Zero Level Set'-Shot Learning of Shape Signed Distance Functions in Feature Space"
Pytorch Implementation of INR-based codec RECOMBINER (Robust and Enhanced Compression with Bayesian Implicit Neural Representations)
Add a description, image, and links to the implicit-neural-representation topic page so that developers can more easily learn about it.
To associate your repository with the implicit-neural-representation topic, visit your repo's landing page and select "manage topics."