Neural-Sorcerer
Master's degree student at "Computer Science and Engineering" with focus on AI Computer Vision areas. Expertise: ML-DL with PyTorch/TensorFlow/Scikit‑Learn.
DeltaX (AI Company)Seoul
Pinned Repositories
3DDFA_V2
The official PyTorch implementation of Towards Fast, Accurate and Stable 3D Dense Face Alignment, ECCV 2020.
6DRepNet
Official Pytorch implementation of 6DRepNet: 6D Rotation representation for unconstrained head pose estimation.
Albumentations-image-augmentation
Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
Awesome-Multi-Task-Learning
An up-to-date list of works on Multi-Task Learning
BOKAS
cleanlab
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
cocoapi
COCO API - Dataset @ http://cocodataset.org/
courses
This repository is a curated collection of links to various courses and resources about Artificial Intelligence (AI)
daily-coding-problem
Solutions to problems sent by dailycodingproblem.com
MMDetection
OpenMMLab Detection Toolbox and Benchmark
Neural-Sorcerer's Repositories
Neural-Sorcerer/3DDFA_V2
The official PyTorch implementation of Towards Fast, Accurate and Stable 3D Dense Face Alignment, ECCV 2020.
Neural-Sorcerer/6DRepNet
Official Pytorch implementation of 6DRepNet: 6D Rotation representation for unconstrained head pose estimation.
Neural-Sorcerer/Awesome-Multi-Task-Learning
An up-to-date list of works on Multi-Task Learning
Neural-Sorcerer/cocoapi
COCO API - Dataset @ http://cocodataset.org/
Neural-Sorcerer/courses
This repository is a curated collection of links to various courses and resources about Artificial Intelligence (AI)
Neural-Sorcerer/cvat
Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale.
Neural-Sorcerer/Depth-Anything
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation
Neural-Sorcerer/diffusion-models-class
Materials for the Hugging Face Diffusion Models Course
Neural-Sorcerer/edgeai-mmdetection
Train Lite (Embedded Friendly) Object Detection models using https://github.com/open-mmlab/mmdetection
Neural-Sorcerer/edgeai-modelzoo
AI / Deep Neural Network Models and Examples
Neural-Sorcerer/insightface
State-of-the-art 2D and 3D Face Analysis Project
Neural-Sorcerer/KD_Lib
A Pytorch Knowledge Distillation library for benchmarking and extending works in the domains of Knowledge Distillation, Pruning, and Quantization.
Neural-Sorcerer/MDT
Masked Diffusion Transformer is the SOTA for image synthesis. (ICCV 2023)
Neural-Sorcerer/MMAction2-action-recognition
OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark
Neural-Sorcerer/Neural-Sorcerer.github.io
Neural-Sorcerer/onnx-simplifier
Simplify your onnx model
Neural-Sorcerer/PIPNet
Efficient facial landmark detector
Neural-Sorcerer/pytorch-cifar
95.47% on CIFAR10 with PyTorch
Neural-Sorcerer/PyTorch-Computer-Vision-Cookbook
PyTorch Computer Vision Cookbook, Published by Packt
Neural-Sorcerer/PyTorchVideo-action-recognition
A deep learning library for video understanding research.
Neural-Sorcerer/quantization-notes
Notes on quantization in neural networks
Neural-Sorcerer/Test
This is new repositiary
Neural-Sorcerer/torchserve_video_inference
Serve, optimize and scale PyTorch models in production
Neural-Sorcerer/TorchVision-pytorch-image-models
Datasets, Transforms and Models specific to Computer Vision
Neural-Sorcerer/ultralytics
NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite
Neural-Sorcerer/vcard-personal-portfolio
vCard is a fully responsive personal portfolio website, responsive for all devices.
Neural-Sorcerer/YOLOv8
YOLOv8 implementation without DFL using PyTorch
Neural-Sorcerer/YOLOv8-human
YOLOv8 re-implementation for human detection using PyTorch
Neural-Sorcerer/YOLOv8-qat
Quantization Aware Training
Neural-Sorcerer/yolov9
Implementation of paper - YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information