Action Generation
35 papers with code • 0 benchmarks • 3 datasets
Benchmarks
These leaderboards are used to track progress in Action Generation
HumanAct12
PHSPD
Two4Two
Most implemented papers
Mapping Instructions to Actions in 3D Environments with Visual Goal Prediction
We propose to decompose instruction execution to goal prediction and action generation.
Human Action Generation with Generative Adversarial Networks
xingchenzhao/Generating-Human-Skeletons-with-Mutual-Actions-WGAN-Pytorch
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Inspired by the recent advances in generative models, we introduce a human action generation model in order to generate a consecutive sequence of human motions to formulate novel actions.
AutoScraper: A Progressive Understanding Web Agent for Web Scraper Generation
In this work, we introduce the paradigm of generating web scrapers with LLMs and propose AutoScraper, a two-stage framework that can handle diverse and changing web environments more efficiently.
Flow Q-Learning
seohongpark/fql
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We present flow Q-learning (FQL), a simple and performant offline reinforcement learning (RL) method that leverages an expressive flow-matching policy to model arbitrarily complex action distributions in data.
Efficient Motion Planning for Automated Lane Change based on Imitation Learning and Mixed-Integer Optimization
Traditional motion planning methods suffer from several drawbacks in terms of optimality, efficiency and generalization capability.
Learning Diverse Stochastic Human-Action Generators by Learning Smooth Latent Transitions
zheshiyige/Learning-Diverse-Stochastic-Human-Action-Generators-by-Learning-Smooth-Latent-Transitions
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AAAI 2019
In this paper, we focus on skeleton-based action generation and propose to model smooth and diverse transitions on a latent space of action sequences with much lower dimensionality.
Graph Constrained Reinforcement Learning for Natural Language Action Spaces
rajammanabrolu/KG-A2C
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ICLR 2020
Interactive Fiction games are text-based simulations in which an agent interacts with the world purely through natural language.
Structure-Aware Human-Action Generation
PingYu-iris/SA-GCN
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ECCV 2020
Generating long-range skeleton-based human actions has been a challenging problem since small deviations of one frame can cause a malformed action sequence.
Action2Motion: Conditioned Generation of 3D Human Motions
EricGuo5513/action-to-motion
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Action recognition is a relatively established task, where givenan input sequence of human motion, the goal is to predict its ac-tion category.
Keep CALM and Explore: Language Models for Action Generation in Text-based Games
princeton-nlp/calm-textgame
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EMNLP 2020
In this paper, we propose the Contextual Action Language Model (CALM) to generate a compact set of action candidates at each game state.
