We present MotionDiffuser, a diffusion based representation for the joint distribution of future
trajectories over multiple agents. Such representation has several key advantages: first, our …

Talking head synthesis is a promising approach for the video production industry. Recently,
a lot of effort has been devoted in this research area to improve the generation quality or …

Anomalies are rare and anomaly detection is often therefore framed as One-Class
Classification (OCC), ie trained solely on normalcy. Leading OCC techniques constrain the …

Stochastic human motion prediction (HMP) has generally been tackled with generative
adversarial networks and variational autoencoders. Most prior works aim at predicting highly …

Diffusion-based generative models have recently emerged as powerful solutions for high-
quality synthesis in multiple domains. Leveraging the bidirectional Markov chains, diffusion …

Hand motion prediction from both first-and third-person perspectives is vital for enhancing
user experience in AR/VR and ensuring safe remote robotic arm control. Previous works …

Predicting human motion plays a crucial role in ensuring a safe and effective human-robot
close collaboration in intelligent remanufacturing systems of the future. Existing works can …

Existing motion forecasting models, while making progress, struggle to bridge the gap
between the source and target domains. Recent solutions often rely on an unrealistic …

Accurate human trajectory prediction is crucial for applications such as autonomous
vehicles, robotics, and surveillance systems. Yet, existing models often fail to fully leverage …

The ability of intelligent systems to predict human behaviors is crucial, particularly in fields
such as autonomous vehicle navigation and social robotics. However, the complexity of …