ABiFN: Attention‐based bi‐modal fusion network for object detection at night time

Camera‐based object detection in low‐light/night‐time conditions is a fundamental problem because of insufficient lighting. So far, a mid‐level fusion of RGB and thermal images is done to complement each other's features. In this work, an attention‐based bi‐modal fusion network is proposed for a better object detection in the thermal domain by integrating a channel‐wise attention module. The experimental results show that the proposed framework improves the mAP by 4.13 points on the FLIR dataset.