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Found 13 papers, 0 papers with code
CLR-GAM: Contrastive Point Cloud Learning with Guided Augmentation and Feature Mapping
Point cloud data plays an essential role in robotics and self-driving applications.
DRAMA: Joint Risk Localization and Captioning in Driving
We make this data available to the community for further research.
LOKI: Long Term and Key Intentions for Trajectory Prediction
We also propose a model that jointly performs trajectory and intention prediction, showing that recurrently reasoning about intention can assist with trajectory prediction.
RAIN: Reinforced Hybrid Attention Inference Network for Motion Forecasting
Motion forecasting plays a significant role in various domains (e. g., autonomous driving, human-robot interaction), which aims to predict future motion sequences given a set of historical observations.
Shared Cross-Modal Trajectory Prediction for Autonomous Driving
At test time, a single input modality (e. g., LiDAR data) is required to generate predictions from the input perspective (i. e., in the LiDAR space), while taking advantages from the model trained with multiple sensor modalities.
Social-STAGE: Spatio-Temporal Multi-Modal Future Trajectory Forecast
This paper considers the problem of multi-modal future trajectory forecast with ranking.
SSP: Single Shot Future Trajectory Prediction
Third, the semantic context of the scene are modeled and take into account the environmental constraints that potentially influence the future motion.
Shared Cross-Modal Trajectory Prediction for Autonomous Driving
At test time, a single input modality (e. g., LiDAR data) is required to generate predictions from the input perspective (i. e., in the LiDAR space), while taking advantages from the model trained with multiple sensor modalities.
TITAN: Future Forecast using Action Priors
In an attempt to address this problem, we introduce TITAN (Trajectory Inference using Targeted Action priors Network), a new model that incorporates prior positions, actions, and context to forecast future trajectory of agents and future ego-motion.
NEMO: Future Object Localization Using Noisy Ego Priors
In the proposed approach, a predictive distribution of future forecast is jointly modeled with the uncertainty of predictions.
DROGON: A Trajectory Prediction Model based on Intention-Conditioned Behavior Reasoning
We propose a Deep RObust Goal-Oriented trajectory prediction Network (DROGON) for accurate vehicle trajectory prediction by considering behavioral intentions of vehicles in traffic scenes.
The H3D Dataset for Full-Surround 3D Multi-Object Detection and Tracking in Crowded Urban Scenes
Finally, sources of errors are discussed for the development of future algorithms.
Semi-supervised Learning: Fusion of Self-supervised, Supervised Learning, and Multimodal Cues for Tactical Driver Behavior Detection
First, predefined driving behaviors are sparse in a naturalistic driving setting.
