Research Article
SENetCount: An Optimized Encoder-Decoder Architecture with Squeeze-and-Excitation for Crowd Counting
Table 1
Summary of some state-of-the-art methods.
| Methods | Year and venue | Architecture | Inference manner | Learning paradigm |
| MCNN [9] | 2016 CVPR | Multicolumn | Whole image | Single-task | ic-CNN [10] | 2018 ECCV | Multicolumn | Whole image | Multitask | SAAN [11] | 2019 WACV | Multicolumn | Whole image | Single-task | SPN [12] | 2019 WACV | Single-column | Whole image | Single-task | LA-Batch [13] | 2022 TPAMI | Single-column | Patch | Multi-task | MANet [14] | 2021 CIAN | Single-column | Whole image | Single-task | LSC-CNN [15] | 2021 TPAMI | Multicolumn | Whole image | Multitask (include detection) | AutoScale [16] | 2022 IJCV | Multicolumn | Patch | Multitask (include detection) |
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