1 code implementation • 11 Feb 2023 • Dawei Dai, Yutang Li, Liang Wang, Shiyu Fu, Shuyin Xia, Guoyin Wang
In this study, we proposed a new task named sketch less face image retrieval (SLFIR), in which the retrieval was carried out at each stroke and aim to retrieve the target face photo using a partial sketch with as few strokes as possible (see Fig. 1).
no code implementations • COLING 2018 • Yue Gu, Kangning Yang, Shiyu Fu, Shuhong Chen, Xinyu Li, Ivan Marsic
The proposed hybrid attention architecture helps the system focus on learning informative representations for both modality-specific feature extraction and model fusion.
no code implementations • ACL 2018 • Yue Gu, Kangning Yang, Shiyu Fu, Shuhong Chen, Xinyu Li, Ivan Marsic
Multimodal affective computing, learning to recognize and interpret human affects and subjective information from multiple data sources, is still challenging because: (i) it is hard to extract informative features to represent human affects from heterogeneous inputs; (ii) current fusion strategies only fuse different modalities at abstract level, ignoring time-dependent interactions between modalities.