lonl Goto Github PK

adam2020

Solution to MICCAI 2020 ADAM

advsemiseg

Adversarial Learning for Semi-supervised Semantic Segmentation, BMVC 2018

awesome-satellite-imagery-competitions

List of machine learning competitions for satellite imagery and remote sensing.

bdd_driving_model

cdbn

Convolutional Deep Belief Networks with 'MATLAB','MEX','CUDA' versions

coach

Reinforcement Learning Coach by Intel® Nervana™ enables easy experimentation with state of the art Reinforcement Learning algorithms

countseg

Official code for "Object counting and instance segmentation with image-level supervision", in CVPR 2019

cross_view_slam

dataset

dcamnet

Correlation and Attention Mechanism based Network for Change Detection

deepmapping

code/webpage for the DeepMapping project

deepvoxels

dll

Deep Learning Library (DLL) for C++

dmtrl

[Code] Deep Multi-task Representation Learning: A Tensor Factorisation Approach

domain-transfer-network

TensorFlow Implementation of "Unsupervised Cross-Domain Image Generation"

droins

Aerial image change detection using dual regions of interest networks

fbow

FBOW (Fast Bag of Words) is an extremmely optimized version of the DBow2/DBow3 libraries.

gdas

PyTorch implementation of "Searching for A Robust Neural Architecture in Four GPU Hours", CVPR 2019

generative-models

Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

georef_imageregistration

grass

GRASS GIS - free and open source Geographic Information System (GIS)

grid-r-cnn

hdml

Implementation of Hardness-Aware Deep Metric Learning (CVPR 2019 Oral) in Tensorflow.

hmmn

HMMN: Online metric learning for human re-identification via hard sample mining memory network

leveraging-crowdsourced-gps-data-for-road-extraction-from-aerial-imagery

The source code of CVPR 2019 paper "Leveraging Crowdsourced GPS Data for Road Extraction from Aerial Imagery"

lm_nav

locating-objects-without-bboxes

PyTorch code for "Locating objects without bounding boxes" - Loss function and trained models

lonl.github.io

mar

Pytorch code for our CVPR'19 (oral) work: Unsupervised person re-identification by soft multilabel learning

metric-learning-divide-and-conquer

Source code for the paper "Divide and Conquer the Embedding Space for Metric Learning", CVPR 2019