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Bartosz Ludwiczuk (melgor)

melgor

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Company:BLCV

Location:Poland, Poznan

Home Page:http://blcv.pl/static/index.html

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Bartosz Ludwiczuk's repositories

DRAW

Torch implementation of DRAW: A Recurrent Neural Network For Image Generation, based on https://github.com/vivanov879/draw

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Triplet-Learning

Training code to reproduce FaceNet

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kaggle-whale-tail

25th solution for the Kagge Competition https://www.kaggle.com/c/humpback-whale-identification

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FV-Benchmark

Face Verification Benchmarks (LFW, BLUFR). Mainly for testing Deep Learning nets learned by Caffe

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Face-Verification

Framework for Face-Verification

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Apollo

Repository for National Data Science Bowl competition (Kaggle), 23th positions

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jointCascade_py

Joint Cascade Face Detection and Alignment

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autograd

Efficiently computes derivatives of numpy code.

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blcv.github.io

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caffe

Caffe: a fast framework for deep learning. For the most recent version checkout the dev branch. For the latest stable release checkout the master branch.

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CRFasRNN-merge

This is a repository forked from the latest official caffe-master on Jun 23, 2016. And I merged the latest code of CRFasRNN with it. I have simply tested the code, and it worked right. But there is no guarantee for the merge.

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DLDD

Distance Learning using Deep Learning

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examples

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image-processing-pipeline

Modular image processing pipeline using OpenCV and Python generators

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liblinear

LibLinear 1.96 + MakeFile for creating library

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LucekLib

Straightforward implementation of Neural Nets

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melgor.github.io

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metric_learning.pytorch

Metric Learing Library containing state-of-the-art algorithms

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openface

Face recognition with deep neural networks.

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pytorch-image-models

PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more

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pytorch-unsupervised-segmentation

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research-ms-loss

MS-Loss: Multi-Similarity Loss for Deep Metric Learning

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resnet-kaggle

Repo for Kaggle-StateFarm competition

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torch-TripletEmbedding

TripletLoss used in Google's FaceNet paper

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Visual-Product-Recognition-2023

Solution for 2nd place in Visual Product Recognition Challenge 2023

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