Learning Cross-Modal Deep Representations for Robust Pedestrian Detection
Learning Cross-Modal Deep Representations for Robust Pedestrian Detection
This paper presents a novel method for detecting pedestrians under adverse illumination conditions. Our approach relies on a novel cross-modality learning framework and it is based on two main phases. First, given a multimodal dataset, a deep convolutional network is employed to learn a non-linear mapping, modeling the relations between …