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Found 8 papers, 3 papers with code
Goal-driven Self-Attentive Recurrent Networks for Trajectory Prediction
Human trajectory forecasting is a key component of autonomous vehicles, social-aware robots and advanced video-surveillance applications.
How many Observations are Enough? Knowledge Distillation for Trajectory Forecasting
To this end, we conceive a novel distillation strategy that allows a knowledge transfer from a teacher network to a student one, the latter fed with fewer observations (just two ones).
SlowFast Rolling-Unrolling LSTMs for Action Anticipation in Egocentric Videos
Action anticipation in egocentric videos is a difficult task due to the inherently multi-modal nature of human actions.
AC-VRNN: Attentive Conditional-VRNN for Multi-Future Trajectory Prediction
Anticipating human motion in crowded scenarios is essential for developing intelligent transportation systems, social-aware robots and advanced video surveillance applications.
Knowledge Distillation for Action Anticipation via Label Smoothing
Since multiple actions may equally occur in the future, we treat action anticipation as a multi-label problem with missing labels extending the concept of label smoothing.
A CNN-RNN Framework for Image Annotation from Visual Cues and Social Network Metadata
Images represent a commonly used form of visual communication among people.
Social and Scene-Aware Trajectory Prediction in Crowded Spaces
Mimicking human ability to forecast future positions or interpret complex interactions in urban scenarios, such as streets, shopping malls or squares, is essential to develop socially compliant robots or self-driving cars.
3-D Hand Pose Estimation from Kinect's Point Cloud Using Appearance Matching
We present a novel appearance-based approach for pose estimation of a human hand using the point clouds provided by the low-cost Microsoft Kinect sensor.
