FAAC: Facial Animation Generation with Anchor Frame and Conditional Control for Superior Fidelity and Editability

no code implementations • 6 Dec 2023 • Linze Li, Sunqi Fan, Hengjun Pu, Zhaodong Bing, Yao Tang, Tianzhu Ye, Tong Yang, Liangyu Chen, Jiajun Liang

Our method's efficacy has been validated on multiple representative DreamBooth and LoRA models, delivering substantial improvements over the original outcomes in terms of facial fidelity, text-to-image editability, and video motion.

Face Model Video Generation

Efficient One Pass Self-distillation with Zipf's Label Smoothing

1 code implementation • 26 Jul 2022 • Jiajun Liang, Linze Li, Zhaodong Bing, Borui Zhao, Yao Tang, Bo Lin, Haoqiang Fan

This paper proposes an efficient self-distillation method named Zipf's Label Smoothing (Zipf's LS), which uses the on-the-fly prediction of a network to generate soft supervision that conforms to Zipf distribution without using any contrastive samples or auxiliary parameters.