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 with no code
Towards more realistic human motion prediction with attention to motion coordination
However, the motion coordination, a global joint relation reflecting the simultaneous cooperation of all joints, is usually weakened because it is learned from part to whole progressively and asynchronously.
Gaze-guided Hand-Object Interaction Synthesis: Benchmark and Method
Here, the object motion diffusion model generates sequences of object motions based on gaze conditions, while the hand motion diffusion model produces hand motions based on the generated object motion.
Human Motion Prediction under Unexpected Perturbation
We investigate a new task in human motion prediction, which is predicting motions under unexpected physical perturbation potentially involving multiple people.
Existence Is Chaos: Enhancing 3D Human Motion Prediction with Uncertainty Consideration
We believe our work could provide a novel perspective to consider the uncertainty quality for the general motion prediction task and encourage the studies in this field.
Fooling Neural Networks for Motion Forecasting via Adversarial Attacks
Human motion prediction is still an open problem, which is extremely important for autonomous driving and safety applications.
AdvMT: Adversarial Motion Transformer for Long-term Human Motion Prediction
To achieve seamless collaboration between robots and humans in a shared environment, accurately predicting future human movements is essential.
GazeMoDiff: Gaze-guided Diffusion Model for Stochastic Human Motion Prediction
Human motion prediction is important for virtual reality (VR) applications, e. g., for realistic avatar animation.
Recent Advances in Deterministic Human Motion Prediction: A Review
In recent years, with the continuous advancement of deep learning and the emergence of large-scale human motion datasets, human motion prediction technology has gradually gained prominence in various fields such as human-computer interaction, autonomous driving, sports analysis, and personnel tracking.
Dynamic Dense Graph Convolutional Network for Skeleton-based Human Motion Prediction
Graph Convolutional Networks (GCN) which typically follows a neural message passing framework to model dependencies among skeletal joints has achieved high success in skeleton-based human motion prediction task.
Orientation-Aware Leg Movement Learning for Action-Driven Human Motion Prediction
Specifically, we follow a two-stage forecasting strategy by first employing the motion diffusion model to generate the target motion with a specified future action, and then producing the in-betweening to smoothly connect the observation and prediction to eventually address motion prediction.
