badtobest / badtobest.github.io

BadToBest 团队主页

BadToBest Team

We are a group of algorithm engineers from the Terminal Technology Department of Ant Group, and we are very pleased to communicate with everyone.

Open Source Projects

Publications

1. Chen, Z., Cao, J., Chen, Z., Li, Y., & Ma, C. (2024). EchoMimic: Lifelike Audio-Driven Portrait Animations through Editable Landmark Conditions. arXiv preprint arXiv:2407.08136.
2. Chai, W., Zheng, D., Cao, J., Chen, Z., Wang, C., & Ma, C. (2023). SpeedUpNet: A Plug-and-Play Hyper-Network for Accelerating Text-to-Image Diffusion Models. arXiv preprint arXiv:2312.08887.
3. Cao, J., Liu, Y., Bai, W., Ding, J., & Li, L. (2023, June). Nasty-SFDA: Source free domain adaptation from a nasty model. In ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 1-5). IEEE.
4. Xu, Y., Meng, L., Peng, R., Yin, Y., Ding, J., Li, L., & Wu, D. (2023, June). Cross-Modal Diversity-Based Active Learning for Multi-Modal Emotion Estimation. In 2023 International Joint Conference on Neural Networks (IJCNN) (pp. 1-8). IEEE.
5. Li, S., Xu, Y., Wu, H., Wu, D., Yin, Y., Cao, J., & Ding, J. (2022, October). Facial Expression Recognition In-the-Wild with Deep Pre-trained Models. In European Conference on Computer Vision (pp. 181-190). Cham: Springer Nature Switzerland.
6. Xu, Y., Cui, Y., Jiang, X., Yin, Y., Ding, J., Li, L., & Wu, D. (2022). Inconsistency-based multi-task cooperative learning for emotion recognition. IEEE Transactions on Affective Computing, 13(4), 2017-2027.
7. Li, S., Xu, Y., Wu, H., Wu, D., Yin, Y., Cao, J., & Ding, J. (2022, October). Facial Expression Recognition In-the-Wild with Deep Pre-trained Models. In European Conference on Computer Vision (pp. 181-190). Cham: Springer Nature Switzerland.
8. Wang, L., Chen, Z., Yu, T., Ma, C., Li, L., & Liu, Y. (2022). Faceverse: a fine-grained and detail-controllable 3d face morphable model from a hybrid dataset. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (pp. 20333-20342).
9. Cao, J., Liu, Y., Ding, J., & Li, L. (2022, October). Self-supervised face anti-spoofing via anti-contrastive learning. In Chinese Conference on Pattern Recognition and Computer Vision (PRCV) (pp. 479-491). Cham: Springer Nature Switzerland.
10. Li, S., Xu, Y., Wu, H., Wu, D., Yin, Y., Cao, J., & Ding, J. (2022). Facial affect analysis: Learning from synthetic data & multi-task learning challenges. arXiv preprint arXiv:2207.09748.
11. Liu, Y., Cao, J., Li, B., Hu, W., Ding, J., & Li, L. (2022). Cross-architecture knowledge distillation. In Proceedings of the Asian conference on computer vision (pp. 3396-3411).
12. Zheng, D., Liu, Y., & Li, L. (2022). Leveraging inter-layer dependency for post-training quantization. Advances in Neural Information Processing Systems, 35, 6666-6679.