Lei Li's repositories
OpenPCDet
OpenPCDet Toolbox for LiDAR-based 3D Object Detection.
Image-processing-algorithm
paper implement
TNN
TNN: developed by Tencent Youtu Lab and Guangying Lab, a lightweight and high-performance deep learning framework for mobile inference. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework. TNN：由腾讯优图实验室和光影实验室协同打造，移动端高性能、轻量级推理框架，同时拥有跨平台、高性能、模型压缩、代码裁剪等众多突出优势。TNN框架在原有Rapidnet、ncnn框架的基础上进一步加强了移动端设备的支持以及性能优化，同时也借鉴了业界主流开源框架高性能和良好拓展性的优点。目前TNN已经在手Q、微视、P图等应用中落地，欢迎大家参与协同共建，促进TNN推理框架进一步完善。
MNN
MNN is a blazing fast, lightweight deep learning framework, battle-tested by business-critical use cases in Alibaba
ncnn
ncnn is a high-performance neural network inference framework optimized for the mobile platform
Play-Leetcode
My Solutions to Leetcode problems. All solutions support C++ language, some support Java and Python. Multiple solutions will be given by most problems. Enjoy:) 我的Leetcode解答。所有的问题都支持C++语言，一部分问题支持Java语言。近乎所有问题都会提供多个算法解决。大家加油！：）
mace
MACE is a deep learning inference framework optimized for mobile heterogeneous computing platforms.
tensorflow
An Open Source Machine Learning Framework for Everyone
Image-Contrast-Enhancement
C++ implementation of several image contrast enhancement techniques.
embedded-ai.bench
benchmark for embededded-ai deep learning inference engines, such as NCNN / TNN / MNN / TensorFlow Lite etc.
Play-with-Data-Structures
Codes of my MOOC Course <Play Data Structures in Java>. Updated contents and practices are also included. 我在慕课网上的课程《Java语言玩转数据结构》示例代码。课程的更多更新内容及辅助练习也将逐步添加进这个代码仓。
ClassificationForAndroid
在Android使用深度学习模型实现图像识别，本项目提供了多种使用方式，使用到的框架如下：Tensorflow Lite、Paddle Lite、MNN、TNN
awesome_list
awesome_list
FALSR
Fast, Accurate and Lightweight Super-Resolution models
OptimizedImageEnhance
Several image/video enhancement methods, implemented by Java, to tackle common tasks, like dehazing, denoising, backscatter removal, low illuminance enhancement, featuring, smoothing and etc.
FSRCNN-pytorch
PyTorch implementation of Accelerating the Super-Resolution Convolutional Neural Network (ECCV 2016)
awesome-super-resolution
A curated list of awesome super resolution resources
Neural-Networks-on-Silicon
This is a collection of works on neural networks and neural accelerators.
awesome-architecture-search
A curated list of awesome architecture search resources
contextualLoss
The Contextual Loss
VideoSuperResolution
A collection of state-of-the-art video or single-image super-resolution architectures, reimplemented in tensorflow.
reproducible-image-denoising-state-of-the-art
Collection of popular and reproducible image denoising works.
Deformable-ConvNets
Deformable Convolutional Networks
Single-Image-Super-Resolution
A collection of high-impact and state-of-the-art SR methods
neural-architecture-search
Basic implementation of [Neural Architecture Search with Reinforcement Learning](https://arxiv.org/abs/1611.01578).