AREL
Story generator
This codebase provides an implementation of a novel adversarial reward learning algorithm for generating human-like visual stories from image sequences.
Code for the ACL paper "No Metrics Are Perfect: Adversarial Reward Learning for Visual Storytelling"
136 stars
12 watching
35 forks
Language: Python
last commit: about 4 years ago adversarial-learningadversarial-reward-learninginverse-reinforcement-learningrlvision-and-languagevisual-storytelling
Related projects:
| Repository | Description | Stars |
|---|---|---|
 eric-wallace/universal-triggers | A toolkit for generating and analyzing adversarial triggers in natural language processing models. | 295 |
 alex-petrenko/sample-factory | A high-throughput reinforcement learning library with optimized synchronous and asynchronous implementations of policy gradients. | 839 |
 iffix/machin | An open-source reinforcement learning library for PyTorch, providing a simple and clear implementation of various algorithms. | 402 |
 qdata/adversarialdnn-playground | An online tool allowing users to visualize and generate adversarial examples to deceive neural networks | 130 |
 maluuba/geneva_datasets | Scripts to generate datasets for an image generation task using Generative Adversarial Networks and deep learning techniques | 37 |
 tristandeleu/pytorch-maml-rl | Replication of Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks in PyTorch for reinforcement learning tasks | 830 |
 humancompatibleai/imitation | Provides clean implementations of imitation and reward learning algorithms | 1,350 |
 juliareinforcementlearning/reinforcementlearninganintroduction.jl | Provides Julia code to generate figures and examples for an introductory reinforcement learning book | 309 |
 ashual/scene_generation | A PyTorch implementation of a deep learning-based method for generating interactive scenes with specified object attributes and relations | 188 |
 jakezhaojb/arae | An implementation of Adversarially Regularized Autoencoders for language generation and discrete structure modeling. | 400 |
 jind11/textfooler | A tool for generating adversarial examples to attack text classification and inference models | 496 |
 securitygames/oef | Provides tools and algorithms for developing reinforcement learning policies in game environments. | 3 |
 uclanlp/elmo-c | Efficient Contextual Representation Learning Model with Continuous Outputs | 4 |
 eleurent/rl-agents | A collection of implementations of Reinforcement Learning and planning algorithms in Python. | 596 |
 aboev/arae-tf | Automates generation of discrete sequence text using adversarially regularized autoencoders | 20 |