Name
Abstract | ||
|---|---|---|
A robust facial landmark detection framework is proposed in this paper, which can be trained in an end-to-end fashion and has achieved promising detection accuracy in the 3rd Grand Challenge of 106-Point Facial Landmark Localization. Firstly, the upper bound of computational complexity is 100MFLOPs and the model size is 2MB, we design a new model named ShuffleNeXt to be the backbone. Based on Shuf... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICMEW53276.2021.9455973 | 2021 IEEE International Conference on Multimedia & Expo Workshops (ICMEW) |
Keywords | DocType | ISSN |
Location awareness,Training,Heating systems,Quantization (signal),Upper bound,Convolution,Computational modeling | Conference | 2330-7927 |
ISBN | Citations | PageRank |
978-1-6654-4989-2 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shenqi Lai | 1 | 63 | 5.67 |
| Lei Liu | 2 | 0 | 0.34 |
| Zhenhua Chai | 3 | 12 | 6.59 |
| Xiaolin Wei | 4 | 7 | 8.27 |