SEPT: Towards Efficient Scene Representation Learning for Motion Prediction

26 September 2023

Papers citing "SEPT: Towards Efficient Scene Representation Learning for Motion Prediction"

7 / 7 papers shown

Title
Structure-preserving contrastive learning for spatial time series Yiru Jiao S. Cranenburgh Simeon C. Calvert H. Lint AI4TS 92 0 0 10 Feb 2025
Target-driven Self-Distillation for Partial Observed Trajectories Forecasting Pengfei Zhu Peng Shu Mengshi Qi Liang Liu Huadong Ma 76 0 0 28 Jan 2025
Snapshot: Towards Application-centered Models for Pedestrian Trajectory Prediction in Urban Traffic Environments Nico Uhlemann Yipeng Zhou Tobias Mohr Markus Lienkamp 65 1 0 10 Jan 2025
EDRF: Enhanced Driving Risk Field Based on Multimodal Trajectory Prediction and Its Applications Junkai Jiang Zeyu Han Yuning Wang Mengchi Cai Qingwen Meng Qing Xu Jianqiang Wang 19 1 0 19 Oct 2024
SmartPretrain: Model-Agnostic and Dataset-Agnostic Representation Learning for Motion Prediction Yang Zhou Hao Shao Letian Wang Steven Waslander Hongsheng Li Yu Liu 36 2 0 11 Oct 2024
Traj-MAE: Masked Autoencoders for Trajectory Prediction Hao Chen Jiaze Wang Kun Shao Furui Liu Jianye Hao Chenyong Guan Guangyong Chen Pheng-Ann Heng 57 38 0 12 Mar 2023
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 305 7,443 0 11 Nov 2021