This repo contains the work done for CMSC 828I.It showcases a basic concept of a Implicit Neural Representation for a Single Image

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

FunctaFormer is a novel, domain-agnostic super-resolution method that leverages Implicit Neural Representations (INRs) to upscale diverse data types, including images, audio, videos, 3D shapes, manifold data, and LiDAR scans.

Learning KAN-based Implicit Neural Representations for Deformable Image Registration

Pytorch3d rendering an visualization basics

SAD-SLAM: Sign-Agnostic Dynamic Simultaneous Localization and Mapping

Repository containing code for Siamese SIREN: Audio Compression with Implicit Neural Representations. Published as a workshop paper at ICML 2023 neural compression workshop.

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.

Siamese Wavelet SLAM: Real-Time 3D Mapping for Autonomous Vehicles with Signed Distance Function and Neural Point

An implicit neural representation framework to correct motion artifacts from CT. Author: Zhennong Chen, PhD

Implementation of "FLOWING 🌊: Implicit Neural Flows for Structure-Preserving Morphing", to appear on NeurIPS 2025

[MICCAI 2024] TrIND: Representing Anatomical Trees by Denoising Diffusion of Implicit Neural Fields

[AAAI-2024] Official Pytorch implementation of "ColNeRF: Collaboration for Generalizable Sparse Input Neural Radiance Field"

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).

Website of SmartSplat

A fast coordinate-based neural video encoder

An expandable sandbox for experimentation with Neural Radiance Fields and implicit representations

Framework for training implicit neural representations

[ICCV 2023] Curvature-Aware Training for Coordinate Networks

ADL4CV 2023 project