Fine-Grained Vehicle Detection (FGVD) is a dataset for fine-grained vehicle detection captured from a moving camera mounted on a car. The FGVD dataset is challenging as it has vehicles in complex traffic scenarios with intra-class and inter-class variations in types, scale, pose, occlusion, and lighting conditions.

It contains 5502 scene images with 210 unique fine- grained labels of multiple vehicle types organized in a three-level hierarchy. While previous classification datasets also include makes for different kinds of cars, FGVD introduces new class labels for categorizing two-wheelers, autorickshaws, and trucks.