Learning-Resources

Links to some of the papers, repos and other materials arranged by subject

Subjects

Visual Object Tracking

1. https://www.votchallenge.net/vot2020/trackers.html (Source codes from VOT 2020)

2. https://github.com/visionml/pytracking (ETH Zurich Tracker Repository)

3. Siamese Natural Language Tracker: https://github.com/fredfung007/snlt

Neuro-Imaging

1. https://medium.com/coinmonks/visualizing-brain-imaging-data-fmri-with-python-e1d0358d9dba

2. https://medium.com/coinmonks/visualizing-brain-imaging-data-fmri-with-python-c68fcd595d5f

3. https://medium.com/coinmonks/visualizing-brain-imaging-data-fmri-with-python-3e1899d1e212

Event Camera

1. https://github.com/uzh-rpg/event-based_vision_resources (ETH Zurich)

Image Correspondence/Optical Flow

1. https://github.com/XiSHEN0220/RANSAC-Flow (RANSAC-FLOW*)

2. https://github.com/NVlabs/PWC-Net?utm_source=catalyzex.com (PWC-Net)

3. https://github.com/voxelmorph/voxelmorph (3D - Data)

4. https://github.com/airlab-unibas/airlab (AIRLAB - 2D and 3D data)

5. Learning-based Image Registration with Meta-Regularization

6. https://github.com/PruneTruong/DenseMatching (GOCOR/PDCNET)

Super Resolution

1. https://github.com/sefibk/KernelGAN (KernelGAN: state of the art non-blind SR Technique)

2. https://github.com/yuanjunchai/IKC (IKC: state of the art non-blind SR Technique)

Misc.

1. https://github.com/wvangansbeke/Unsupervised-Classification (Unsupervised Classification)

2. https://github.com/ruoqi-liu/DeepIPW (Deep learning framework for drug repurposing)

3. https://energy-based-models.github.io/?fbclid=IwAR3NXZDs1N49Ehcq4cVjLPIIbl_lWBWZn5FTb_nvH-ckX_f3UdHJB1v_S_U (Energy Based Models)

Programming and Tools

PyTorch

1. https://jovian.ai/learn/deep-learning-with-pytorch-zero-to-gans (Basics)

2. https://nn.labml.ai/index.html (PyTorch Neural Networks Implementations)

3. https://atcold.github.io/pytorch-Deep-Learning/ (SPRING 2020 · NYU CENTER FOR DATA SCIENCE)

Julia

1. https://alan-turing-institute.github.io/DataScienceTutorials.jl/ (Basics)

2. https://towardsdatascience.com/machine-learning-in-julia-5bca700e0348 (ML in Julia)

Data Visualization

1. https://jovian.ai/aakashns/dataviz-cheatsheet

Tools

1. Train Code Generator - https://github.com/jrieke/traingenerator

2. Annotation Tool - https://github.com/heartexlabs/label-studio

3. Image Pre-Processing for DL (PyTorch): https://albumentations.ai/docs/examples/pytorch_classification/

4. GitHub Apps Dev: https://streamlit.io/