Scale-Aware Trident Networks for Object Detection

Understand

Scale variation is one of the key challenges in object detection.

• In this work, we first present a controlled experiment to investigate the effect of receptive fields for scale variation in object detection.
• Based on the findings from the exploration experiments, we propose a novel Trident Network (TridentNet) aiming to generate scale-specific feature maps with a uniform representational power.
• We construct a parallel multi-branch architecture in which each branch shares the same transformation parameters but with different receptive fields.