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Name: Lukas Hedegaard

Type: User

Company: Aarhus University

Bio: Deep Learning Researcher

Location: Aarhus, Denmark

👋 Hi, I'm Lukas Hedegaard

PostDoc at Aarhus University, Denmark researching Deep Learning, network acceleration and Transfer Learning applied to Computer Vision and Natural Language Processing. Recent works include:

Hedegaard et al.: "Continual Spatio-Temporal Graph Convolutional Networks (Pattern Recognition, 2023)
Hedegaard et al.: "Continual Transformers: Redundancy-Free Attention for Online Inference" (ICLR, 2023)
Hedegaard & Iosifidis: "Continual 3D Convolutional Neural Networks for Real-time Processing of Videos" (ECCV, 2022)
Hedegaard & Iosifidis: "Continual Inference: A Library for Efficient Online Inference with Deep Neural Networks in PyTorch" (ECCV workshop, 2022)
Hedegaard et al.: "Supervised Domain Adaptation: A Graph Embedding Perspective and a Rectified Experimental Protocol" (Transactions on Image Processing, 2021)
Hedegaard et al.: "Supervised Domain Adaptation using Graph Embedding" (ICPR, 2021)
Heidari et al.: "Graph Convolutional Networks" (Deep Learning for Robot Perception and Cognition, 2022)
Hedegaard et al.: "Human Activity Recognition" (Deep Learning for Robot Perception and Cognition, 2022)
Hedegaard et al.: "Structured Pruning Adapters" (preprint, 2023)

Apart from doing ML research projects (like real-time Human Activity Recognition using CoX3D ☝️), I like to package code up nicely and open-source whenever it may be of value. Open-source libraries include:

Continual Inference [🐍, C++] - Building blocks for Continual Inference Networks in PyTorch.
Ride [🐍] - Training wheels, side rails, and helicopter parent for your Deep Learning projects in PyTorch.
OpenDR [🐍, C++] - A modular, open and non-proprietary toolkit for core robotic functionalities by harnessing deep learning.
DatasetOps [🐍] - Fluent dataset operations, compatible with your favorite libraries.
PyTorch Benchmark [🐍] - Easily benchmark PyTorch model FLOPs, latency, throughput, allocated gpu memory and energy consumption.
Co-Rider [🐍] - Tiny configuration library tailored for the Ride ecosystem.
Supers [🐍] - Call a function in all superclasses using supers(self).foo(42).
react-native-svg-pan-zoom [JS] - Pan-zoom via two-finger "Google Maps"-style pinch and drag gestures.
redux-maybe [JS] - Nodejs Package for attaching callback functions to redux messages.
redux-blabber [JS] - Redux store enhancer for synchronizing states and actions across store instances.

Find me 🌐

Lukas Hedegaard's Projects

activitynet

This repository is intended to host tools and demos for ActivityNet

block-spa-experiments

Block Sparse movement pruning

ccsa

"Unified Deep Supervised Domain Adaptation and Generalization" (ICCV 2017)

channel-spa-experiments

Experiments for channel-based Structured Pruning Adapters

cloth-segmentation

This repo contains code and a pre-trained model for clothes segmentation.

co-rider

Tiny configuration library tailored for the Ride ecosystem

co3d

Official source code for "Continual 3D Convolutional Neural Networks for Real-time Processing of Videos" [ECCV2022]

continual-inference

A Python library for Continual Inference Networks in PyTorch

continual-skeletons

Official codebase for "Online Skeleton-based Action Recognition with Continual Spatio-Temporal Graph Convolutional Networks"

continual-transformers

Official Pytorch Implementation for "Continual Transformers: Redundancy-Free Attention for Online Inference" [ICLR 2023]

continual-transformers-tf

TensorFlow implementation of Continual Transformer building blocks

continual_inference_sphinx_theme

cooadtr

Ablation study for "OadTR: Online Action Detection with Transformers".

dage

Official TensorFlow implementation for "Supervised Domain Adaptation: A Graph Embedding Perspective and a Rectified Experimental Protocol" [TIP 2021] and "Supervised Domain Adaptation using Graph Embedding" [ICPR 2020]