Human motion prediction
59 papers with code • 0 benchmarks • 4 datasets
Action prediction is a pre-fact video understanding task, which focuses on future states, in other words, it needs to reason about future states or infer action labels before the end of action execution.
Benchmarks
These leaderboards are used to track progress in Human motion prediction
EMDB
GTA-IM Dataset
VIENA2
Latest papers
Context-based Interpretable Spatio-Temporal Graph Convolutional Network for Human Motion Forecasting
Human motion prediction is still an open problem extremely important for autonomous driving and safety applications.
GCNext: Towards the Unity of Graph Convolutions for Human Motion Prediction
The past few years has witnessed the dominance of Graph Convolutional Networks (GCNs) over human motion prediction. Various styles of graph convolutions have been proposed, with each one meticulously designed and incorporated into a carefully-crafted network architecture.
MoMask: Generative Masked Modeling of 3D Human Motions
For the base-layer motion tokens, a Masked Transformer is designated to predict randomly masked motion tokens conditioned on text input at training stage.
Dynamic Compositional Graph Convolutional Network for Efficient Composite Human Motion Prediction
oliviazwy/dcgcn
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With potential applications in fields including intelligent surveillance and human-robot interaction, the human motion prediction task has become a hot research topic and also has achieved high success, especially using the recent Graph Convolutional Network (GCN).
InterDiff: Generating 3D Human-Object Interactions with Physics-Informed Diffusion
Sirui-Xu/InterDiff
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ICCV 2023
This paper addresses a novel task of anticipating 3D human-object interactions (HOIs).
Multiscale Residual Learning of Graph Convolutional Sequence Chunks for Human Motion Prediction
Our experiments on two challenging benchmark datasets, CMU Mocap and Human3. 6M, demonstrate that our proposed method is able to effectively model the sequence information for motion prediction and outperform other techniques to set a new state-of-the-art.
Auxiliary Tasks Benefit 3D Skeleton-based Human Motion Prediction
mediabrain-sjtu/auxformer
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ICCV 2023
To work with auxiliary tasks, we propose a novel auxiliary-adapted transformer, which can handle incomplete, corrupted motion data and achieve coordinate recovery via capturing spatial-temporal dependencies.
Spatio-Temporal Branching for Motion Prediction using Motion Increments
Human motion prediction (HMP) has emerged as a popular research topic due to its diverse applications, but it remains a challenging task due to the stochastic and aperiodic nature of future poses.
Physics-constrained Attack against Convolution-based Human Motion Prediction
Specifically, we introduce a novel adaptable scheme that facilitates the attack to suit the scale of the target pose and two physical constraints to enhance the naturalness of the adversarial example.
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.
