no code implementations • 22 Nov 2024 • Yiyang Cai, Zhengkai Jiang, Yulong Liu, Chunyang Jiang, Wei Xue, Wenhan Luo, Yike Guo
Facial personalization represents a crucial downstream task in the domain of text-to-image generation.
1 code implementation • 2 Nov 2023 • Hanwen Chang, Haihao Shen, Yiyang Cai, Xinyu Ye, Zhenzhong Xu, Wenhua Cheng, Kaokao Lv, Weiwei Zhang, Yintong Lu, Heng Guo
Diffusion models have gained popularity for generating images from textual descriptions.
1 code implementation • 17 Oct 2023 • Wenhua Cheng, Yiyang Cai, Kaokao Lv, Haihao Shen
As large language models (LLMs) become more prevalent, there is a growing need for new and improved quantization methods that can meet the computationalast layer demands of these modern architectures while maintaining the accuracy.
2 code implementations • 11 Sep 2023 • Wenhua Cheng, Weiwei Zhang, Haihao Shen, Yiyang Cai, Xin He, Kaokao Lv, Yi Liu
Large Language Models (LLMs) have demonstrated exceptional proficiency in language-related tasks, but their deployment poses significant challenges due to substantial memory and storage requirements.
no code implementations • 11 Aug 2023 • Yiyang Cai, Jiaming Lu, Jiewen Wang, Shuang Liang
UACTN decouples the representation learning of sketches and 3D shapes into two separate tasks: classification-based sketch uncertainty learning and 3D shape feature transfer.
2 code implementations • CVPR 2022 • Licheng Tang, Yiyang Cai, Jiaming Liu, Zhibin Hong, Mingming Gong, Minhu Fan, Junyu Han, Jingtuo Liu, Errui Ding, Jingdong Wang
Instead of explicitly disentangling global or component-wise modeling, the cross-attention mechanism can attend to the right local styles in the reference glyphs and aggregate the reference styles into a fine-grained style representation for the given content glyphs.