Search Results for author:
Found 3 papers, 2 papers with code
Depth Prompting for Sensor-Agnostic Depth Estimation
Through this embedding process, our method helps the pretrained model to be free from restraint of depth scan range and to provide absolute scale depth maps.
Learning Pedestrian Group Representations for Multi-modal Trajectory Prediction
A key idea of GP-Graph is to model both individual-wise and group-wise relations as graph representations.
Non-Probability Sampling Network for Stochastic Human Trajectory Prediction
Capturing multimodal natures is essential for stochastic pedestrian trajectory prediction, to infer a finite set of future trajectories.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
