MegEngine

#计算机科学#YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/

#计算机科学#MegEngine 是一个快速、可拓展、易于使用且支持自动求导的深度学习框架

#计算机科学#Official MegEngine implementation of CREStereo(CVPR 2022 Oral).

#计算机科学#Efficient ML solution for long-tailed demands.

采用MegEngine实现的各种主流深度学习模型

#计算机科学#Official MegEngine implementation of RepLKNet

ECCV2020 - Practical Deep Raw Image Denoising on Mobile Devices

NBNet: Noise Basis Learning for Image Denoising with Subspace Projection

#自然语言处理#Python package containing all custom layers used in Neural Networks (Compatible with PyTorch, TensorFlow and MegEngine)

MegEngine implementation of YOLOX

The official MegEngine implementation of the ECCV 2022 paper: Ghost-free High Dynamic Range Imaging with Context-aware Transformer

MegEngine到其他框架的转换器

Insertion sequences (Insertion Element) [https://en.wikipedia.org/wiki/Insertion_sequence] collected from ISfinder (https://isfinder.biotoul.fr/)

This is the official implementation of the paper "Instance-conditional Knowledge Distillation for Object Detection", based on MegEngine and Pytorch.

The official MegEngine implementation of the ICCV 2021 paper: GyroFlow: Gyroscope-Guided Unsupervised Optical Flow Learning

Official MegEngine implementation of ECCV2022 "D2C-SR: A Divergence to Convergence Approach for Real-World Image Super-Resolution".

RAW-based blind denoising, 1st place in MegCup 2022 (Team Feedback)

#计算机科学#OMNet: Learning Overlapping Mask for Partial-to-Partial Point Cloud Registration, ICCV 2021, MegEngine implementation.

MegEngine Official Documentation

Official implementation of the FST-Matching Model.