zhangxiaohan123

Awesome-Dynamic-Point-Cloud-Analysis

Video-Captioning

video-classification

TensorFlow implementation for video classification.

Point-Spatio-Temporal-Convolution

Implementation of the "PSTNet: Point Spatio-Temporal Convolution on Point Cloud Sequences" paper.

neuronaldynamics-exercises

Python exercises accompanying the book "Neuronal Dynamics"

PointRNN-PyTorch

PointRNN, PointGRU and PointLSTM.

LPFC

The codes were written for the following paper: Yim MY, Cai X & Wang X-J(2019) Transforming the choice outcome to an action plan in monkey lateral prefrontal cortex: a neural circuit model. Neuron 103, 1–13.

argoverse_baselinetracker

Baseline tracker code release for the paper Argoverse: 3D Tracking and Forecasting With Rich Maps, CVPR 2019.

Recurrent-Attention-Model

Tensorflow implementation of paper "Recurrent Models of Visual Attention"

Unsupervised-Person-Re-identification-Clustering-and-Fine-tuning

PointRNN

TensorFlow implementation of PointRNN, PointGRU and PointLSTM.

slimmable_networks

Slimmable Networks, AutoSlim, and Beyond, ICLR 2019, and ICCV 2019

AutoDL-Projects

Automated deep learning algorithms implemented in PyTorch.

pyGAT

Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)

dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

darts

Differentiable architecture search for convolutional and recurrent networks

ai-deadlines

:alarm_clock: AI conference deadline countdowns

ZSL_GAN

Code for the paper CVPR‘18 "A Generative Adversarial Approach for Zero-Shot Learning from Noisy Texts"

maml

Code for "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"

DN4

Pytorch code of "Revisiting Local Descriptor based Image-to-Class Measure for Few-shot Learning", CVPR 2019.

MetaOptNet

Meta-Learning with Differentiable Convex Optimization (CVPR 2019 Oral)

maxl

The implementation of "Self-Supervised Generalisation with Meta Auxiliary Learning" [NeurIPS 2019].

GraphTSNE

PyTorch Implementation of GraphTSNE, ICLR’19

GNNPapers

Must-read papers on graph neural networks (GNN)

bert

TensorFlow code and pre-trained models for BERT

Graph-WaveNet

graph wavenet

benchmark

TorchBench is a collection of open source benchmarks used to evaluate PyTorch performance.