Andrew-Zhu

3D-MSNet

A point cloud based deep learning model for untargeted feature detection and quantification in profile LC-HRMS data

Explainable_GEC

The official code of the 2023 ACL paper "Enhancing Grammatical Error Correction Systems with Explanations"

GenImage

VanillaNet

poolformer

PoolFormer: MetaFormer Is Actually What You Need for Vision (CVPR 2022 Oral)

Pretrained-IPT

ComVEX

Implementations of Recent Papers in Computer Vision

Pruning

Code for "Co-Evolutionary Compression for Unpaired Image Translation" (ICCV 2019), "SCOP: Scientific Control for Reliable Neural Network Pruning" (NeurIPS 2020) and “Manifold Regularized Dynamic Network Pruning” (CVPR 2021).

ml-visuals

🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.

Awesome-Pruning

A curated list of neural network pruning resources.

transformer-in-transformer

Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image classification, in Pytorch

d2l-pytorch

This project reproduces the book Dive Into Deep Learning (https://d2l.ai/), adapting the code from MXNet into PyTorch.

Efficient-AI-Backbones

Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.

pytorch-mot-tracking

Demo the Kalman Filter on pedestrian tracking with YOLOv3.

self-critical.pytorch

Unofficial pytorch implementation for Self-critical Sequence Training for Image Captioning. and others.

DenseVideoCaptioning

Official Tensorflow Implementation of the paper "Bidirectional Attentive Fusion with Context Gating for Dense Video Captioning" in CVPR 2018, with code, model and prediction results.

RedCNN

BSN-boundary-sensitive-network

Codes of our paper: "BSN: Boundary Sensitive Network for Temporal Action Proposal Generation"

video-caption.pytorch

pytorch implementation of video captioning

video-caption-openNMT.pytorch

implement video caption based on openNMT

mace

MACE is a deep learning inference framework optimized for mobile heterogeneous computing platforms.

handong1587.github.io

tiny

Tiny Face Detector, CVPR 2017

gender-classification

I have performed Gender Classification from static images using 5 different classifiers. They are Linear Discriminant Analysis, K-Nearest neighbors, Support Vector Machines, Naive Bayes and Decision tree learning. I was able to determine Gender of a person with accuracy of 98.75% (using Linear Discriminant Analysis).

HDC.caffe

Complete Code for "Hard-Aware-Deeply-Cascaded-Embedding"