Junxiao Shen's Academic Page

OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark

HoloLens 2 Sensor Streaming.

🦄 State-of-the-Art Conversational AI with Transfer Learning

Motion imitation with deep reinforcement learning.

Skeleton-based Action Recognition

集成了Tensorflow 2版本的端到端语音识别模型，并且RTF(实时率)在0.1左右/Mandarin State-of-the-art Automatic Speech Recognition in Tensorflow 2

PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks

A lightweight network for body/hand action recognition

IndicSwipe is a collection of datasets and neural model architectures for decoding swipe gesture inputs on touch-based Indic language keyboards across 7 languages.

Use Convolutional Recurrent Neural Network to recognize the Handwritten line text image without pre segmentation into words or characters. Use CTC loss Function to train.

Online Hand Writing Recognition using BLSTM

Recognizing Swiping Gestures on a touchscreen using SHARK2 Decoder

A TensorFlow implementation of DeepMind's WaveNet paper

Small-footprint Keyword Spotting

"Handwriting Recognition in Low-resource Scripts using Adversarial Learning ”, IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2019.

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

Code for "Deep Convolutional Networks as shallow Gaussian Processes"

MSR Action Recognition Datasets and Codes

MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville

A Chinese Deep Speech Recognition System 包括基于深度学习的声学模型和基于深度学习的语言模型

Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

An implementation of an Evolution Strategy and a Tabu Search for 4M17 coursework submission

Collection of optimisation algorithms used for 4m17

Jupyter notebooks (Python) for the course 3M1 at the Department of Engineering, University of Cambridge

Non official project based on original /r/Deepfakes thread. Many thanks to him!