23 Open source projects that are alternatives of or similar to FREE

A curated list of papers, code and resources pertaining to weak-shot classification, detection, and segmentation.

General-Purpose Neural Networks for Sentence Boundary Detection

Codes for ACL-IJCNLP 2021 Paper "Zero-shot Fact Verification by Claim Generation"

Zero Shot Learning with Feature Generating Networks

Official PyTorch code for the ICIP 2021 paper 'Syntactically Guided Generative Embeddings For Zero Shot Skeleton Action Recognition'

零样本学习

NLU: domain-intent-slot; text2SQL

A Visual-semantic embedding model using word2vec and CNNs

Out-of-Distribution Detection for Generalized Zero-Shot Action Recognition

[ECCV 2020] Official Pytorch implementation for "Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification". SOTA results for ZSL and GZSL

Unofficial Implementation of Zero-Shot Text-to-Speech for Text-Based Insertion in Audio Narration

A python ZSL system which makes it easy to run Zero-Shot Learning on new datasets, by giving it features and attributes. Used for the paper "Zero-Shot Learning Based Approach For Medieval Word Recognition Using Deep-Learned Features", published in ICFHR2018.

Dialogue Knowledge Transfer Networks (DiKTNet)

Codes for the CVPR 2021 paper: Contrastive Embedding for Generalized Zero-Shot Learning

"Good Robot! Now Watch This!": Repurposing Reinforcement Learning for Task-to-Task Transfer; and “Good Robot!”: Efficient Reinforcement Learning for Multi-Step Visual Tasks with Sim to Real Transfer

Class Normalization for Continual Zero-Shot Learning

A collection of AWESOME things about domian adaptation

Awesome Domain Adaptation Python Toolbox

Official Pytorch Implementation of: "Semantic Diversity Learning for Zero-Shot Multi-label Classification"(ICCV, 2021) paper

Zero-shot image tagging by hierarchical semantic embedding

Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling

No description or website provided.

[ECCV 2018] code for Choose Your Neuron: Incorporating Domain Knowledge Through Neuron Importance