ConvLSTM-AE_VAD_ICME2017 (code reimplementation)

总结梳理自然语言处理工程师(NLP)需要积累的各方面知识，包括面试题，各种基础知识，工程能力等等，提升核心竞争力

Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.

刷算法全靠套路，认准 labuladong 就够了！English version supported! Crack LeetCode, not only how, but also why.

This is a zoo which contain all kinds of video prediction model code(reimplementation or author provide)and the paper.I created this repository to make it easy for newbies in the video prediction f…

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

Guide for both TensorFlow and PyTorch in comparative way

Code for SIGGRAPH 2020 paper "RigNet: Neural Rigging for Articulated Characters"

Depth-Aware Video Frame Interpolation (CVPR 2019)

A Dynamical Atoms-Based Network For Video Prediction

Image-to-Image Translation in PyTorch

Deep Learning Experiment Management

Implements the unsupervised pre-training of convolutional neural networks

Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

A mix of GAN implementations including progressive growing

PySlowFast: video understanding codebase from FAIR for reproducing state-of-the-art video models.

A highly efficient implementation of Gaussian Processes in PyTorch

MemAE for anomaly detection. -- Gong, Dong, et al. "Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection". ICCV 2019.

Latex code for making neural networks diagrams

Efficiently computes derivatives of NumPy code.

A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch

PyTorch DataLoaders implemented with DALI for accelerating image preprocessing

Drawing Bayesian networks, graphical models, tensors, technical frameworks, and illustrations in LaTeX.

Code examples in pyTorch and Tensorflow for CS230

Displays all the 2019 CVPR Accepted Papers in a way that they are easy to parse.

A curated list of awesome self-supervised methods

PyTorch Tutorial for Deep Learning Researchers

A curated list of awesome anomaly detection resources