1 code implementation • 30 Aug 2023 • Yi Ding, Su Zhang, Chuangao Tang, Cuntai Guan
A natural method is to learn the temporal dynamic patterns.
no code implementations • Proceedings of the ACM Web Conference 2022 • Ying Li, Ye Tao, Su Zhang, Zhirong Hou, Zhonghai Wu
We train a model that integrates information from the user-item interaction graph and the user-user social graph and train two auxiliary models that only use one of the above graphs respectively.
1 code implementation • 24 Mar 2022 • Su Zhang, Ruyi An, Yi Ding, Cuntai Guan
The visual encoding from the visual block is concatenated with the attention feature to emphasize the visual information.
1 code implementation • 2 Jul 2021 • Su Zhang, Yi Ding, Ziquan Wei, Cuntai Guan
We propose an audio-visual spatial-temporal deep neural network with: (1) a visual block containing a pretrained 2D-CNN followed by a temporal convolutional network (TCN); (2) an aural block containing several parallel TCNs; and (3) a leader-follower attentive fusion block combining the audio-visual information.
2 code implementations • 7 Apr 2021 • Yi Ding, Neethu Robinson, Su Zhang, Qiuhao Zeng, Cuntai Guan
TSception consists of dynamic temporal, asymmetric spatial, and high-level fusion layers, which learn discriminative representations in the time and channel dimensions simultaneously.
no code implementations • 5 Sep 2019 • Jake Sherman, Chinmay Shukla, Rhonda Textor, Su Zhang, Amy A. Winecoff
Critical to addressing these issues in fashion recommendation is an evaluation strategy that: 1) includes multiple metrics that are relevant to fashion, and 2) is performed within segments of users with different interaction histories.
no code implementations • ICCV 2017 • Su Zhang, Yang Yang, Kun Yang, Yi Luo, Sim-Heng Ong
We present a new point set registration method with global-local correspondence and transformation estimation (GL-CATE).