A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is
FETNet: Feature Exchange Transformer Network for RGB-D Object Detection
British Machine Vision Conference
In RGB-D object detection, due to the inherent difference between the RGB and Depth modalities, it remains challenging to simultaneously leverage sensed photometric and depth information. In this paper, to address this issue, we propose a Feature Exchange Transformer Network (FETNet), which consists of two well-designed components: the Feature Exchange Module (FEM), and the Multi-modal Vision Transformer (MViT). Specially, we propose the FEM to exchange part of the channels between RGB anddblp:conf/bmvc/XiaoXXW21 fatcat:tysgc73d4bfk3o6yprboaolfjm