[ECCV 2024 Oral] DriveLM: Driving with Graph Visual Question Answering

In this project, I used Python and TensorFlow to classify traffic signs. Dataset used: German Traffic Sign Dataset. This dataset has more than 50,000 images of 43 classes. I was able to reach a +99% validation accuracy, and a 97.3% testing accuracy.

🌐 3D and 4D World Modeling: A Survey

End to End Autopilot Perception Playbook

Website of the SegmentMeIfYouCan benchmark.

My personal website

Countdown for all* relevant conferences in the domain of autonomous driving

📐 Personal GitHub web page. Based on the minimal-mistakes Jekyll theme.

A framework for the analysis of trust in the interaction between pedestrians and vehicle (manual and automated), from the perspective of the driver of a manual or an automated vehicle, using a crowdsourcing approach.

🌐 A curated collection of vision-language-action (VLA) models for autonomous driving applications

Inspired by comma.ai OpenPilot idea, this is an AD Autopilot on RaspberryPi based on ROS called RosPilot. The project currently performs lane follow feature. The codebase is written to be modular, enable quick prototyping and facilitate learning and collaboration across multiple users. The hardware used so far is the donkey car robocar + RPI 3

Lokale Navigation von Mikromobilitätsfahrzeugen mittels Reinforcement Learning

Multi-Object Tracking and Trajectory Prediction. This repository contains all codes written for SUMMER RESEARCH INTERNSHIP (2021) at AI and Robotics Park (ARTPARK), IISc Bangalore

Jekyll code for the website Computationally Thinking Blog

🌍 Discover advancements in 3D scene understanding with LiDAR techniques for semantic and panoptic segmentation, plus occupancy prediction.

Project on detecting lane lines on roads in a video stream, using polynomials

This is a Deep Learning Project to classify German Road Signs using deep neural networks and image processing.

Comparing the performance of MPC based racing and RL based racing

[Small] Traffic sign classification using Tensorflow and LeNet.

Computer vision project on vehicle detection and tracking on roads