COTTA: Context-Aware Transfer Adaptation for Trajectory Prediction in Autonomous Driving

1. 1Collect and analyze trajectory data from diverse environments
2. 2Develop and train a context-aware model using transfer learning
3. 3Adapt the model to new environments using COTTA
4. 4Evaluate and refine the model's performance in various scenarios

AI engineers and researchers working on autonomous driving projects can benefit from COTTA to improve the accuracy of trajectory prediction models in diverse environments

💡 Transfer learning and context-aware adaptation can improve trajectory prediction accuracy in diverse environments

💡 COTTA: Context-Aware Transfer Adaptation for Trajectory Prediction in Autonomous Driving