Fabian Herzog (fubel)

fubel

Geek Repo

Company:@virtualstaging-ai

Location:Munich

Home Page:fabianherzog.me

Twitter:@fub3l

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Fabian Herzog's repositories

sparselandtools

:sparkles: A Python package for sparse representations and dictionary learning, including matching pursuit, K-SVD and applications.

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synthehicle

[WACVW 2023] A massive synthetic dataset for 3D multi-target multi-camera tracking and segmentation.

PyCannyEdge

Educational Python implementation of the Canny Edge Detector

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PeronaMalikDiffusion

Python implementation of the Perona-Malik anisotropic filter for denoising and edge detection

stmodeling

Code for the paper "Comparative Analysis of CNN-based Spatiotemporal Reasoning in Videos"

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Deep-Learning-Papers-Reading-Roadmap

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

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website

Kubeflow's public website

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AIC21-MTMC

🏆The 1st place solution of track3 (City-Scale Multi-Camera Vehicle Tracking) in the NVIDIA AI City Challenge at CVPR 2021 Workshop.

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bounding-box-prediction-RL

Bounding box prediction in Object Tracking using Reinforcement Learning

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deep-learning-project-template

Pytorch Lightning code guideline for conferences

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gmm-torch

Gaussian mixture models in PyTorch.

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Kalman-and-Bayesian-Filters-in-Python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

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Neural-Decision-Forests

An implementation of the Deep Neural Decision Forests in PyTorch

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open-reid

Open source person re-identification library in python

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pymvg

Python Multi-View Geometry

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python-docs-samples

Code samples used on cloud.google.com

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pytorch-template

PyTorch deep learning projects made easy.

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reid-strong-baseline

Bag of Tricks and A Strong Baseline for Deep Person Re-identification

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Towards-Realtime-MOT

Joint Detection and Embedding for fast multi-object tracking

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TrackEval

HOTA (and other) evaluation metrics for Multi-Object Tracking (MOT).

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tracking_wo_bnw

Implementation of "Tracking without bells and whistles” and the multi-object tracking "Tracktor"

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vision

Datasets, Transforms and Models specific to Computer Vision

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