wenjiaXu

APN-ZSL

This is a PyTorch implementation of the paper "Attribute Prototype Network for Zero-Shot Learning".

VGSE

RS_Scene_ZSL

PyTorch code for Deep Semantic-Visual Alignment for zero-shot remote sensing image scene classification

Optical-RemoteSensing-Image-Resolution

The code for paper "Deep Memory Connected Neural Network for Optical Remote Sensing Image Restoration"

pytorch-LapSRN

Pytorch implementation for LapSRN (CVPR2017)

wenjiaXu.github.io

releasing-research-code

Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)

attribute-label-embedding

An Implementation of Attribute Label Embedding (ALE) method of Zero-Shot Learning

awesome-image-captioning

A curated list of image captioning and related area resources. :-)

awesome-zero-shot-learning

A curated list of papers, code and resources pertaining to zero shot learning

Code-for-STA-Zero-shot-learning

The state-of-the-art code and papers about zero-shot learning

diverse-beam-search

:mag: :shipit: Decoding Diverse Solutions from Neural Sequence Models

DPGN

This repository contains the official implementation of DPGN: Distribution Propagation Graph Network for Few-shot Learning.

FEAT

The code repository for "Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions"

hello-world

the first repository

Python-graph-collection

Collect some useful graphing code for writing papers

pytorch-gve-lrcn

PyTorch implementations for "Generating Visual Explanations" (GVE) and "Long-term Recurrent Convolutional Networks" (LRCN)

resume

An elegant \LaTeX\ résumé template

RISE

Detect model's attention

self-label

Self-labelling via simultaneous clustering and representation learning. (ICLR 2020)

Unsupervised-Classification

SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]

Visual-analytics-and-Interpretability-in-Deep-Learning

本项目主要是通过可视分析的手段，对深度学习的可解释性做出讨论与探讨。并且记录小组成员的学习过程与工作

vqa.pytorch

Visual Question Answering in Pytorch

wDAE_GNN_FewShot

Generating Classification Weights with GNN Denoising Autoencoders for Few-Shot Learning