Detection of main persons in snapshots using deep neural networks
Tatsuya Hamamura, Tomoaki Kimura, Hiroyuki Tsuji · 2021
Detection of main persons in a snapshot is proposed in this paper. The proposed method uses feature maps from Mask RCNN [1] and depth information from the depth estimation model [2] to detect main persons in the photo. Our research aims to construct a deep neural network model to estimate the main person degree map from these two inputs. Based on the estimated importance map, we performed post-processing and confirmed that only important persons could be extracted.