ShairozS
AI scientist doing research in visual object detection/tracking, 3D reconstruction, depth estimation, visual reasoning, and more general deep learning.
Great Falls, Montana
ShairozS's Stars
KindXiaoming/pykan
Kolmogorov Arnold Networks
RepoAnalysis/PythonCloneDetection
Detect semantically similar python code using fine-tuned GraphCodeBERT model.
prokls/cnf-files-download
Download public CNF benchmark files with zsh scripts
Vooban/Smoothly-Blend-Image-Patches
Using a U-Net for image segmentation, blending predicted patches smoothly is a must to please the human eye.
Mstfakts/Building-Detection-MaskRCNN
Building detection from the SpaceNet dataset by using Mask RCNN.
danbochman/SORT
Advanced 'Simple Online Real-Time Tracking' implementation in Python
adipandas/multi-object-tracker
Multi-object trackers in Python
bndr/pipreqs
pipreqs - Generate pip requirements.txt file based on imports of any project. Looking for maintainers to move this project forward.
AnnaManasyan/VICReg
An easy-to-use implementation of VICReg in Pytorch.
imbue-ai/self_supervised
A Pytorch-Lightning implementation of self-supervised algorithms
ayared/Live-Specgram
Real time running spectrogram from local microphone
pytorch/nestedtensor
[Prototype] Tools for the concurrent manipulation of variably sized Tensors.
WestHealth/pyvis
Python package for creating and visualizing interactive network graphs.
adambielski/siamese-triplet
Siamese and triplet networks with online pair/triplet mining in PyTorch
kuangliu/pytorch-cifar
95.47% on CIFAR10 with PyTorch
apple/ml-multiple-futures-prediction
daerduoCarey/partnet_dataset
PartNet Dataset Official Release Repo
iofu728/PaperRead
📒Record some paper read notes
amir-abdi/disentanglement-pytorch
Disentanglement library for PyTorch
eriklindernoren/PyTorch-GAN
PyTorch implementations of Generative Adversarial Networks.
bjkomer/pytorch-legendre-memory-unit
Implementation of the Legendre Memory Unit in PyTorch
marcoemorais/numerics-review
Jupyter notebooks with answers to end of chapter review questions for the textbook Scientific Computing by Michael Heath (2018).
idealo/image-super-resolution
🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.