Contact Us

Address: Industrial Estate, Sector D/1, Allama Iqbal Rd, New Mirpur City, Azad Jammu and Kashmir 10250
Email: fazi_ajku@yahoo.com
Phone: 03125872658


We have collected a vision benchmark suite to detect the static and dynamic objects in the surrounding of our vehicle. The collected dataset exhibits diverse Asian traffic scenarios collected in peak to fewer traffic hours.

This dataset is collected to perform object detection and recognition for the environment perception of self-driving vehicles. It is created over the visual video sequences and 3D point-cloud (1100 KM) of around 80+ cities including dense traffic roads, urban, rural, highways, hilly areas, and motorways.

We have annotated 20,000 images with approximately 55,000 labels presented in 2 types of formats (i.e., Yolo (.txt) and VOC PASCAL (.xml)). This dataset contains diverse class categories including 2-Wheeler (Motorbikes), 3- Wheeler (Rickshaw), and 4+ Wheeler (Cars, Buses, and Trucks).


Lidar Data


HD Camera Data


HD Mapping

Autonomous driving requires in-depth and rigorous analysis of visual scene understanding. Our perception module utilizes the strengths of advanced deep learning methods to boost the object detection performance, which ensures the safety of our vehicles. We have improved the performance capability of our perception module by leveraging the reliable sensor data from our multi-sensor fusion technology. This module can detect and recognize static and dynamic objects in the surrounding of our vehicles. The data received from this module fuels the core decision-making that ascertains the navigation of the vehicle on road.


2d Object Detection


Point Cloud-Based Object Detection


Semantic Segmentation