The IDD95K dataset is an extensive object detection dataset comprising 95,155 images with corresponding annotations provided in JSON formats. The dataset is specifically designed for training and evaluating object detection models across various Indian driving scenes.
Project Aria, in collaboration with IIIT Hyderabad (IIITH), on an exciting initiative aimed at improving driver-assist technologies. The collaboration focuses on using Aria glasses and sensors to gather real-world data to enhance driver behavior analysis, situational awareness, and safety systems. As part of the project, the Aria team visited IIIT Hyderabad in mid August for a series of meetings, presentations, and practical demonstrations.
In an era where technology is rapidly advancing, road safety remains a critical concern. Enter the development of an energy-efficient mmWave radar system, a groundbreaking project designed to enhance road safety and traffic management, regardless of weather conditions. Here’s a glimpse into how this innovative system is set to transform our roads.
The development of reliable and efficient intelligent vehicle systems is dependent on its capability to understand the influence of road and traffic conditions on its own driving actions. This is particularly challenging in developing countries such as India where traffic situations are often dense and unstructured with heterogeneous road occupants.
The Smart City Research Lab at the International Institute of Information Technology (IIIT) Hyderabad developed a hardware system that aims to assist in driving with ease and to reduce accidents. The system is expected to be a low-cost, low-footprint device that can be attached retrospectively to any bike.
IDD-AW is a groundbreaking dataset designed to address the challenges of autonomous driving in adverse weather conditions and unstructured environments. While existing datasets have primarily focused on well-organized, controlled settings, IDD-AW takes a different approach by capturing the complexities of real-world driving scenarios.
