- DFEW [ACM MM 2020]
- FERV39k [CVPR 2022]
- MAFW [ACM MM 2022]
- CAER [ICCV 2021]
- AFEW [IEEE Multimedia 2012]
| Methods | Venues | Years | DFEW | FERV39k | MAFW | |||
|---|---|---|---|---|---|---|---|---|
| UAR | WAR | UAR | WAR | UAR | WAR | |||
| C3D | - | - | 42.74 | 53.54 | 22.68 | 31.69 | 31.17 | 42.25 |
| P3D | - | - | 43.97 | 54.47 | 23.20 | 33.39 | - | - |
| I3D-RGB | - | - | 43.40 | 54.27 | 30.17 | 38.78 | - | - |
| 3D-ResNet18 | - | - | 46.52 | 58.27 | 26.67 | 37.57 | - | - |
| R(2+1)D | - | - | 42.79 | 53.22 | 31.55 | 41.28 | - | - |
| ResNet18-LSTM | - | - | 51.32 | 63.85 | 30.92 | 42.95 | 28.08 | 39.38 |
| R18-ViT | - | - | 55.76 | 67.56 | 38.35 | 48.43 | 35.80 | 47.72 |
| EC-STFL[1] | ACM MM | 2020 | 45.35 | 56.51 | - | - | - | - |
| Former-DFER[2] | ACM MM | 2021 | 53.69 | 65.70 | 37.20 | 46.85 | 31.16 | 43.27 |
| NR-DFERNet[3] | arXiv | 2022 | 54.21 | 68.19 | 33.99 | 45.97 | - | - |
| DPCNet[4] | ACM MM | 2022 | 57.11 | 66.32 | - | - | - | - |
| T-ESFL[5] | ACM MM | 2022 | - | - | - | - | 33.28 | 48.18 |
| EST[6] | PR | 2023 | 53.94 | 65.85 | - | - | - | - |
| Logo-Form[7] | ICASSP | 2023 | 54.21 | 66.98 | 38.22 | 48.13 | - | - |
| GCA+IAL[8] | AAAI | 2023 | 55.71 | 69.24 | 35.82 | 48.54 | - | - |
| CLIPER[9] | arXiv | 2023 | 57.56 | 70.84 | 41.23 | 51.34 | - | - |
| MSCM[10] | PR | 2023 | 58.49 | 70.16 | - | - | - | - |
| AEN[11] | CVPRW | 2023 | 56.66 | 69.37 | 38.18 | 47.88 | - | - |
| M3DFEL[12] | CVPR | 2023 | 56.10 | 69.25 | 35.94 | 47.67 | - | - |
| MAE-DFER[13] | ACM MM | 2023 | 63.41 | 74.43 | 43.12 | 52.07 | 41.62 | 54.31 |
| DFER-CLIP[14] | BMVC | 2023 | 59.61 | 71.25 | 41.27 | 51.65 | 39.89 | 52.55 |
- Jiang X, Zong Y, Zheng W, Tang C, Xia W, Lu C, Liu J. DFEW: A Large-scale Database for Recognizing Dynamic Facial Expressions in the Wild. ACM MM, 2020. [Paper]
- Zhao Z, Liu Q. Former-DFER: Dynamic Facial Expression Recognition Transformer. ACM MM, 2021. [Paper] [Code]
- Li H, Sui M, Zhu Z. NR-DFERNet: Noise-Robust Network for Dynamic Facial Expression Recognition. arXiv, 2022.[Paper]
- Wang Y, Sun Y, Song W, Gao S, Huang Y, Chen Z, Ge W, Zhang W. DPCNet: Dual Path Multi-Excitation Collaborative Network for Facial Expression Representation Learning in Videos. ACM MM, 2022. [Paper]
- Liu Y, Dai W, Feng C, Wang W, Yin G, Zeng J, Shan S. MAFW: A Large-scale, Multi-modal, Compound Affective Database for Dynamic Facial Expression Recognition in the Wild. ACM MM, 2022. [Paper]
- Liu Y, Wang W, Feng C, Zhang H, Chen Z, Zhan Y. Expression snippet transformer for robust video-based facial expression recognition. Pattern Recognition. Pattern Recognition, 2023. [Paper]
- Ma F, Sun B, Li S. Logo-Former: Local-Global Spatio-Temporal Transformer for Dynamic Facial Expression Recognition. ICASSP, 2023. [Paper]
- Li H, Niu H, Zhu Z, Zhao F. Intensity-Aware Loss for Dynamic Facial Expression Recognition in the Wild. AAAI, 2023. [Paper] [Code]
- Li H, Niu H, Zhu Z, Zhao F. CLIPER: A Unified Vision-Language Framework for In-the-Wild Facial Expression Recognition. arXiv, 2023. [Paper]
- Li T, Chan KL, Tjahjadi T. Multi-Scale Correlation Module for Video-based Facial Expression Recognition in the Wild. Pattern Recognition, 2023. [Paper]
- Lee B, Shin H, Ku B, Ko H. Frame Level Emotion Guided Dynamic Facial Expression Recognition With Emotion Grouping. CVPRW, 2023. [Paper]
- Wang H, Li B, Wu S, Shen S, Liu F, Ding S, Zhou A. Rethinking the Learning Paradigm for Dynamic Facial Expression Recognition. CVPR, 2023. [Paper] [Code]
- Sun L, Lian Z, Liu B, Tao J. MAE-DFER: Efficient Masked Autoencoder for Self-supervised Dynamic Facial Expression Recognition. ACM MM, 2023. [Paper] [Code]
- Zhao Z, Patras I. Prompting Visual-Language Models for Dynamic Facial Expression Recognition. BMVC, 2023. [Paper] [Code]