Human activity recognition (HAR) is one of the most important and challenging problems in
the computer vision. It has critical application in wide variety of tasks including gaming …

Robot navigation in crowded public spaces is a complex task that requires addressing a
variety of engineering and human factors challenges. These challenges have motivated a …

Better machine understanding of pedestrian behaviors enables faster progress in modeling
interactions between agents such as autonomous vehicles and humans. Pedestrian …

Pedestrian trajectory prediction is a key technology in autopilot, which remains to be very
challenging due to complex interactions between pedestrians. However, previous works …

Trajectory prediction has been widely pursued in many fields, and many model-based and
model-free methods have been explored. The former include rule-based, geometric or …

Since the past few decades, human trajectory forecasting has been a field of active research
owing to its numerous real-world applications: evacuation situation analysis, deployment of …

Derived from rapid advances in computer vision and machine learning, video analysis tasks
have been moving from inferring the present state to predicting the future state. Vision-based …

To realize trajectory prediction, most previous methods adopt the parameter-based
approach, which encodes all the seen past-future instance pairs into model parameters …

Pedestrian trajectory prediction is an essential and challenging task for a variety of real-life
applications such as autonomous driving and robotic motion planning. Besides generating a …

We propose to forecast future hand-object interactions given an egocentric video. Instead of
predicting action labels or pixels, we directly predict the hand motion trajectory and the …