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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.
T. Hamamura,T. Kimura, andH. Tsuji
"Detection of main persons in snapshots using deep neural networks", Proc. SPIE 11766, International Workshop on Advanced Imaging Technology (IWAIT) 2021, 1176628 (13 March 2021); https://doi.org/10.1117/12.2591000
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T. Hamamura, T. Kimura, H. Tsuji, "Detection of main persons in snapshots using deep neural networks," Proc. SPIE 11766, International Workshop on Advanced Imaging Technology (IWAIT) 2021, 1176628 (13 March 2021); https://doi.org/10.1117/12.2591000