A multi-modal generative model to forecast the future positions of agents in traffics.
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Updated
Aug 12, 2021 - Python
A multi-modal generative model to forecast the future positions of agents in traffics.
Programming contest hosted by CV Zone, sponsored by NVIDIA. Where the objective is to predict the paths of the ball on the pool table and whether they will go in the hole.
I made an educational Rocket Trajectory Simulation Assignment
Implement deep learning based trajectory prediction methods
Code for Bachelor's thesis: Observation of humans using computer vision for autonomous driving
The project involves building a scenario consisting of a Thrower and a Goalie robot arms. The thrower moves to the desired position and throws the ball while the task of the goalie is to intercept and block the incoming ball from making a goal.
Official code for AAAI 2023 paper "Multi-stream Representation Learning for Pedestrian Trajectory Prediction"
Polar Collision Grids: Effective Interaction Modelling for Pedestrian Trajectory Prediction in Shared Space Using Collision Checks (ITSC 2023)
We introduce a novel trajectory predictor that considers social interactions among agents, maintaining spatial-temporal information over an extended temporal horizon. It achieves high accuracy, generalisability, and outperforms recent SOTA algorithms on NGSIM and HIGHD Datasets
Code for "Transformer Networks for 4D Trajectory Prediction"
Vehicle-Pedestrian Motion Prediction using Classification
[under review] Official PyTorch Implementation of "Multi-scale Feature Aggregation Autoregressive Network for Multi-Agent Trajectory Prediction".
Code for "CARPe Posterum: A Convolutional Approach for Real-time Pedestrian Path Prediction"
Modularized, annotated and extended code for LaPred: Lane-Aware Prediction of Multi-Modal Future Trajectories of Dynamic Agents by Kim et al.’s, based on their original implementation.
FIR-based trajectory prediction at nighttime
[T-ITS 2024] TrajPRed: Trajectory Prediction with Region-based Relation Learning
Wondered how your rocket performs under a motor. worry no more! whether you have a commercial off the shelf motor or a custom one, you can easily visualize your rockets performance as long as you have the static fire test results.
Framework for integrating prior knowledge into trajectory prediction models for autonomous driving via Bayesian continual learning.
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