Beyond Bounding Box: Fine-Grained Vehicle Detection via Single Stage Detector with Hierarchical output

Vehicle detection is a crucial module of the camera-based forward collision alert, which is usually used to calculate range and time-to-collision. Conventional methods based on bounding box are too coarse to handle challenging situations such as vehicle pose variations. In this paper, we propose a novel vehicle detector with a fine-grained output representation. The detector exploits a hierarchical tree-like output representation by introducing two subclasses and virtual control points, which not only discriminates each face of a vehicle but also locates their boundaries accurately. Our detector adopts popular single stage multi-scale CNN framework, which is equipped with the hierarchical output, and is beyond the bounding box methods. Experiments on our large-scale self-collected dataset show that our method achieves satisfactory performance.