3 papers
cs.CV2023
Spatial-Temporal Conditional Random Field for Human Trajectory Prediction
Pengqian Han, Jiamou Liu, Jialing He +3
Trajectory prediction is of significant importance in computer vision. Accurate pedestrian trajectory prediction benefits autonomous vehicles and robots in planning their motion. P…
cs.CV2023
STF: Spatial Temporal Fusion for Trajectory Prediction
Pengqian Han, Jiamou Liu, Tianzhe Bao +1
Trajectory prediction is a challenging task that aims to predict the future trajectory of vehicles or pedestrians over a short time horizon based on their historical positions. The…
cs.LG2023
Enhancing Signed Graph Neural Networks through Curriculum-Based Training
Zeyu Zhang, Lu Li, Xingyu Ji +5
Signed graphs are powerful models for representing complex relations with both positive and negative connections. Recently, Signed Graph Neural Networks (SGNNs) have emerged as pot…