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Human action generation
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Yan et al. (2019) CSGN:
"When the dancer is stepping, jumping and spinning on the stage, attentions of all audiences are attracted by the streamof the fluent and graceful movements. Building a model that is capable of dancing is as fascinating a task as appreciating the performance itself. In this paper, we aim to generate long-duration human actions represented as skeleton sequences, e.g. those that cover the entirety of a dance, with hundreds of moves and countless possible combinations."
<span style="color:grey; opacity: 0.6">( Image credit: Convolutional Sequence Generation for Skeleton-Based Action Synthesis )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Agent models: Internalizing Chain-of-Action Generation into Reasoning models
LiteWebAgent: The Open-Source Suite for VLM-Based Web-Agent Applications
FRMD: Fast Robot Motion Diffusion with Consistency-Distilled Movement Primitives for Smooth Action Generation
Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success
VDT-Auto: End-to-end Autonomous Driving with VLM-Guided Diffusion Transformers
Why Are Web AI Agents More Vulnerable Than Standalone LLMs? A Security Analysis
Evolution 6.0: Evolving Robotic Capabilities Through Generative Design
PMAT: Optimizing Action Generation Order in Multi-Agent Reinforcement Learning
SALSA-RL: Stability Analysis in the Latent Space of Actions for Reinforcement Learning
IMLE Policy: Fast and Sample Efficient Visuomotor Policy Learning via Implicit Maximum Likelihood Estimation
Large Language Models for Multi-Robot Systems: A Survey
Flow Q-Learning
Large Action Models: From Inception to Implementation
CARP: Visuomotor Policy Learning via Coarse-to-Fine Autoregressive Prediction
Towards Next-Generation Medical Agent: How o1 is Reshaping Decision-Making in Medical Scenarios
Grounding Video Models to Actions through Goal Conditioned Exploration
Benchmarking Vision, Language, & Action Models on Robotic Learning Tasks
Seg2Act: Global Context-aware Action Generation for Document Logical Structuring
ActionFlow: Equivariant, Accurate, and Efficient Policies with Spatially Symmetric Flow Matching
Affordance-based Robot Manipulation with Flow Matching
EPO: Hierarchical LLM Agents with Environment Preference Optimization
General-purpose Clothes Manipulation with Semantic Keypoints
Wonderful Team: Zero-Shot Physical Task Planning with Visual LLMs
Robots Can Multitask Too: Integrating a Memory Architecture and LLMs for Enhanced Cross-Task Robot Action Generation
Retrieval-Augmented Code Generation for Situated Action Generation: A Case Study on Minecraft
Introducing Brain-like Concepts to Embodied Hand-crafted Dialog Management System
T2LM: Long-Term 3D Human Motion Generation from Multiple Sentences
AutoScraper: A Progressive Understanding Web Agent for Web Scraper Generation
ITCMA: A Generative Agent Based on a Computational Consciousness Structure
AICL: Action In-Context Learning for Video Diffusion Model
Imagine, Initialize, and Explore: An Effective Exploration Method in Multi-Agent Reinforcement Learning
Return-Aligned Decision Transformer
PokeLLMon: A Human-Parity Agent for Pokemon Battles with Large Language Models
Active Generation Network of Human Skeleton for Action Recognition
Large Language Models Empowered Agent-based Modeling and Simulation: A Survey and Perspectives
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