Lip Reading on LRW Word-level (test)
88.8AccuracyStafylakis et al. (WB)
Evaluation Results
| Method | Links | |
|---|---|---|
| Stafylakis et al. (WB)Year=2018, Frontend=ResNet-18, Backend=BiLSTM, Data Type=Lip + Word Boundary, Input Size=112x1122020.11 | 88.8 | |
| Refined Network (SE+MixUp+Cosine LR+LS+WB)Year=2021, Frontend=SE-ResNet-18, Backend=BiGRU, Data Type=Aligned Lip + Word Boundary, Input Size=88x882020.11 | 88.4 | |
| Multi-Stage Distillation (Ma et al.)Year=2020, Frontend=ResNet-18, Backend=MS-TCN, Data Type=Aligned Lip, Input Size=88x882020.11 | 87.7 | |
| Temporal Convolution (Martinez et al.)Year=2020, Frontend=ResNet-18, Backend=MS-TCN, Data Type=Aligned Lip, Input Size=88x882020.11 | 85.3 | |
| Face Cutout (Zhang et al.)Year=2020, Frontend=ResNet-18, Backend=BiGRU, Data Type=Aligned Face, Input Size=112x1122020.11 | 85 | |
| Refined Network (SE+MixUp+Cosine LR+LS+WB)Year=2021, Frontend=SE-ResNet-18, Backend=BiGRU, Data Type=Aligned Lip, Input Size=88x882020.11 | 85 | |
| Mutual Information (Zhao et al.)Year=2020, Frontend=ResNet-18, Backend=BiGRU, Data Type=Lip, Input Size=88x882020.11 | 84.4 | |
| Two Stream (Weng et al.)Year=2019, Frontend=Two-Stream ResNet-18, Backend=BiLSTM, Data Type=Lip, Input Size=112x1122020.11 | 84.1 | |
| Deformation Flow (Xiao et al.)Year=2020, Frontend=ResNet-18, Backend=BiGRU, Data Type=Lip, Input Size=88x882020.11 | 84.1 | |
| Stafylakis et al.Year=2017, Frontend=ResNet-34, Backend=BiLSTM, Data Type=Lip, Input Size=112x1122020.11 | 83.5 | |
| Policy Gradient (Luo et al.)Year=2020, Frontend=ResNet-18, Backend=BiGRU, Data Type=Lip, Input Size=88x882020.11 | 83.5 | |
| Multi-Grained (Wang et al.)Year=2019, Frontend=Multi-Grained ResNet-18, Backend=Conv BiLSTM, Data Type=Lip, Input Size=88x882020.11 | 83.3 | |
| Chung et al.Year=2016, Frontend=VGGM, Data Type=Lip, Input Size=112x1122020.11 | 61.1 |