4 accepted papers
Camouflaged scenes, where objects blend seamlessly into their environments, pose significant challenges to both human observers and computer vision systems. These objects match the background in color, texture, and shape, making them difficult to detect. To this end, we propose leveraging the Segmen…
Co-salient object detection (CoSOD) together with the rapid development of deep learning has led to substantial progress in recent years. However, the feature aggregation between group feature representation and individual feature representation is still a challenging issue. In this work, we propose…
Vehicle re-identification (re-ID) is of great significance to urban operation, management, security and has gained more attention in recent years. However, two critical challenges in vehicle re-ID have primarily been underestimated, i.e., 1): how to make full use of raw data, and 2): how to learn a…
Pedestrian detection methods have been significantly improved with the development of deep convolutional neural networks. Nevertheless, it remains a challenging problem how to robustly detect pedestrians of varied sizes and with occlusions. In this paper, we propose a gated multi-layer convolutional…