Papers Human action generation
“Human action generation” 태그가 달린 논문 13편 · 필터 해제
FinePhys: Fine-grained Human Action Generation by Explicitly Incorporating Physical Laws for Effective Skeletal Guidance
Despite significant advances in video generation, synthesizing physically plausible human actions remains a persistent challenge, particularly in modeling fine-grained semantics and complex temporal dynamics. For instanc…
Action GenerationHuman action generationIn-Context LearningVideo GenerationFLAG3D: A 3D Fitness Activity Dataset with Language Instruction
With the continuously thriving popularity around the world, fitness activity analytic has become an emerging research topic in computer vision. While a variety of new tasks and algorithms have been proposed recently, the…
Action GenerationAction RecognitionHuman action generationHuman Mesh Recovery+1Action-conditioned On-demand Motion Generation
We propose a novel framework, On-Demand MOtion Generation (ODMO), for generating realistic and diverse long-term 3D human motion sequences conditioned only on action types with an additional capability of customization. …
Contrastive LearningDecoderHuman action generationMotion GenerationGenerative Adversarial Graph Convolutional Networks for Human Action Synthesis
Synthesising the spatial and temporal dynamics of the human body skeleton remains a challenging task, not only in terms of the quality of the generated shapes, but also of their diversity, particularly to synthesise real…
Action GenerationDisentanglementDiversityHuman action generation+2MUGL: Large Scale Multi Person Conditional Action Generation with Locomotion
We introduce MUGL, a novel deep neural model for large-scale, diverse generation of single and multi-person pose-based action sequences with locomotion. Our controllable approach enables variable-length generations custo…
Action GenerationDiversityHuman action generationAction-Conditioned 3D Human Motion Synthesis with Transformer VAE
We tackle the problem of action-conditioned generation of realistic and diverse human motion sequences. In contrast to methods that complete, or extend, motion sequences, this task does not require an initial pose or seq…
Action RecognitionDenoisingHuman action generationMotion SynthesisAction2Motion: Conditioned Generation of 3D Human Motions
Action recognition is a relatively established task, where givenan input sequence of human motion, the goal is to predict its ac-tion category. This paper, on the other hand, considers a relativelynew problem, which coul…
Action GenerationHuman action generationStructure-Aware Human-Action Generation
Generating long-range skeleton-based human actions has been a challenging problem since small deviations of one frame can cause a malformed action sequence. Most existing methods borrow ideas from video generation, which…
Action Generationgraph constructionHuman action generationVideo GenerationLearning Diverse Stochastic Human-Action Generators by Learning Smooth Latent Transitions
Human-motion generation is a long-standing challenging task due to the requirement of accurately modeling complex and diverse dynamic patterns. Most existing methods adopt sequence models such as RNN to directly model tr…
Action GenerationDecoderHuman action generationMotion GenerationConvolutional Sequence Generation for Skeleton-Based Action Synthesis
In this work, we aim to generate long actions represented as sequences of skeletons. The generated sequences must demonstrate continuous, meaningful human actions, while maintaining coherence among body parts. Instead of…
Human action generationHuman Action Generation with Generative Adversarial Networks
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. We propose a framework of an aut…
Action GenerationGenerative Adversarial NetworkHuman action generationDeep Video Generation, Prediction and Completion of Human Action Sequences
Current deep learning results on video generation are limited while there are only a few first results on video prediction and no relevant significant results on video completion. This is due to the severe ill-posedness …
Human action generationPredictionVideo GenerationVideo PredictionConditional Generative Adversarial Nets
Generative Adversarial Nets [8] were recently introduced as a novel way to train generative models. In this work we introduce the conditional version of generative adversarial nets, which can be constructed by simply fee…
DescriptiveHuman action generation