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Qu Lei's Projects

baselines icon baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

basicsr icon basicsr

Basic Super-Resolution codes for development. Includes ESRGAN, SFT-GAN for training and testing.

bayesgan icon bayesgan

Tensorflow code for the Bayesian GAN (https://arxiv.org/abs/1705.09558) (NIPS 2017)

bert icon bert

TensorFlow code and pre-trained models for BERT

bert-bilstm-crf-ner icon bert-bilstm-crf-ner

Tensorflow solution of NER task Using BiLSTM-CRF model with Google BERT Fine-tuning And private Server services

betboy icon betboy

Artificial neural networks for predicting results of football(soccer) matches.

bicyclegan icon bicyclegan

[NIPS 2017] Toward Multimodal Image-to-Image Translation

bimef icon bimef

Code and data for the research paper "A Bio-Inspired Multi-Exposure Fusion Framework for Low-light Image Enhancement" (Submitted to IEEE Transactions on Cybernetics)

binary-human-pose-estimation icon binary-human-pose-estimation

This code implements a demo of the Binarized Convolutional Landmark Localizers for Human Pose Estimation and Face Alignment with Limited Resources paper by Adrian Bulat and Georgios Tzimiropoulos.

bing-objectness-1 icon bing-objectness-1

Python implementation of BING Objectness method from "BING: Binarized Normed Gradients for Objectness Estimation at 300fps".

blitznet icon blitznet

Deep neural network for object detection and semantic segmentation in real-time. Official code for the paper "BlitzNet: A Real-Time Deep Network for Scene Understanding"

blockly icon blockly

The web-based visual programming editor.

bobetocalo_eccv18 icon bobetocalo_eccv18

A Deeply-initialized Coarse-to-fine Ensemble of Regression Trees for Face Alignment

caffe icon caffe

Caffe: a fast open framework for deep learning.

caffe-segnet icon caffe-segnet

Implementation of SegNet: A Deep Convolutional Encoder-Decoder Architecture for Semantic Pixel-Wise Labelling

caffe-segnet-cudnn5 icon caffe-segnet-cudnn5

This repository was a fork of BVLC/caffe and includes the upsample, bn, dense_image_data and softmax_with_loss (with class weighting) layers of caffe-segnet (https://github.com/alexgkendall/caffe-segnet) to run SegNet with cuDNN version 5.

caffe-shufflenet icon caffe-shufflenet

This is re-implementation of "ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices"

caiman icon caiman

Computational toolbox for large scale Calcium Imaging Analysis, including movie handling, motion correction, source extraction, spike deconvolution and result visualization.

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