Stochastic Human Motion Prediction
6 papers with code • 0 benchmarks • 0 datasets
Stochastic Human Motion Prediction assumes future stochasticity and therefore tackles the task from a generative point of view. Instead of predicting a single future, it predicts N possible futures.
Benchmarks
These leaderboards are used to track progress in Stochastic Human Motion Prediction
Most implemented papers
Weakly-supervised Action Transition Learning for Stochastic Human Motion Prediction
wei-mao-2019/wat
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CVPR 2022
We introduce the task of action-driven stochastic human motion prediction, which aims to predict multiple plausible future motions given a sequence of action labels and a short motion history.
BeLFusion: Latent Diffusion for Behavior-Driven Human Motion Prediction
BarqueroGerman/BeLFusion
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ICCV 2023
To address these issues, we present BeLFusion, a model that, for the first time, leverages latent diffusion models in HMP to sample from a latent space where behavior is disentangled from pose and motion.
Diverse Human Motion Prediction Guided by Multi-Level Spatial-Temporal Anchors
sirui-xu/stars
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Predicting diverse human motions given a sequence of historical poses has received increasing attention.
CoMusion: Towards Consistent Stochastic Human Motion Prediction via Motion Diffusion
jsun57/comusion
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Stochastic Human Motion Prediction (HMP) aims to predict multiple possible future human pose sequences from observed ones.
Stochastic Multi-Person 3D Motion Forecasting
Sirui-Xu/DuMMF
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This paper aims to deal with the ignored real-world complexities in prior work on human motion forecasting, emphasizing the social properties of multi-person motion, the diversity of motion and social interactions, and the complexity of articulated motion.
Learning Semantic Latent Directions for Accurate and Controllable Human Motion Prediction
Expanding on SLD, we introduce a set of motion queries to enhance the diversity of predictions.
