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Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, i…
This is the project for deep learning in stock market prediction.
Path-Restore: Learning Network Path Selection for Image Restoration (IEEE TPAMI, 2021)
Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.
PyTorch implementation of VSR-Transformer
The code for CVPR21 paper "Deep Animation Video Interpolation in the Wild"
Reference code for the paper: Deep White-Balance Editing (CVPR 2020). Our method is a deep learning multi-task framework for white-balance editing.
Code for C2-Matching (CVPR2021). Paper: Robust Reference-based Super-Resolution via C2-Matching.
AdelaiDet is an open source toolbox for multiple instance-level detection and recognition tasks.
[IJCV] Pyramid Attention Networks for Image Restoration: new SOTA results on multiple image restoration tasks: denoising, demosaicing, compression artifact reduction, super-resolution
[CVPR 2020] 3D Photography using Context-aware Layered Depth Inpainting
A High-Quality Real Time Upscaler for Anime Video
(ECCV 2020) RANSAC-Flow: generic two-stage image alignment
Code for deep generative prior (ECCV2020 oral)
We are building an open database of COVID-19 cases with chest X-ray or CT images.
Deep Unfolding Network for Image Super-Resolution (CVPR, 2020) (PyTorch)
A curated list of resources for Image and Video Deblurring
[CVPR 2020--Oral] CycleISP: Real Image Restoration via Improved Data Synthesis
Code for Rotate-and-Render: Unsupervised Photorealistic Face Rotation from Single-View Images (CVPR 2020)
Depth-Aware Video Frame Interpolation (CVPR 2019)
Fast and Accurate One-Stage Space-Time Video Super-Resolution (accepted in CVPR 2020)
Complete YOLO v3 TensorFlow implementation. Support training on your own dataset.
Minimal PyTorch implementation of YOLOv3
文言文編程語言 A programming language for the ancient Chinese.
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Toward Real-World Single Image Super-Resolution: A New Benchmark and A New Model (ICCV 2019)
Implementation of 'Blind Super-Resolution With Iterative Kernel Correction' (CVPR2019)