Search Results for author: Tao Liang

Found 6 papers, 0 papers with code

Multi-scale Cooperative Multimodal Transformers for Multimodal Sentiment Analysis in Videos

no code implementations16 Jun 2022 Lianyang Ma, Yu Yao, Tao Liang, Tongliang Liu

On the whole, the "multi-scale" mechanism is capable of exploiting the different levels of semantic information of each modality which are used for fine-grained crossmodal interactions.

Multimodal Sentiment Analysis

Expanding Large Pre-Trained Unimodal Models With Multimodal Information Injection for Image-Text Multimodal Classification

no code implementations CVPR 2022 Tao Liang, Guosheng Lin, Mingyang Wan, Tianrui Li, Guojun Ma, Fengmao Lv

Through the proposed MI2P unit, we can inject the language information into the vision backbone by attending the word-wise textual features to different visual channels, as well as inject the visual information into the language backbone by attending the channel-wise visual features to different textual words.

LI-Net: Large-Pose Identity-Preserving Face Reenactment Network

no code implementations7 Apr 2021 Jin Liu, Peng Chen, Tao Liang, Zhaoxing Li, Cai Yu, Shuqiao Zou, Jiao Dai, Jizhong Han

Face reenactment is a challenging task, as it is difficult to maintain accurate expression, pose and identity simultaneously.

Face Reenactment

Attention Is Not Enough: Mitigating the Distribution Discrepancy in Asynchronous Multimodal Sequence Fusion

no code implementations ICCV 2021 Tao Liang, Guosheng Lin, Lei Feng, Yan Zhang, Fengmao Lv

To this end, both the marginal distribution and the elements with high-confidence correlations are aligned over the common space of the query and key vectors which are computed from different modalities.

Time Series Time Series Analysis +1

Weakly-supervised Domain Adaption for Aspect Extraction via Multi-level Interaction Transfer

no code implementations16 Jun 2020 Tao Liang, Wenya Wang, Fengmao Lv

Specifically, the aspect category information is used to construct pivot knowledge for transfer with assumption that the interactions between sentence-level aspect category and token-level aspect terms are invariant across domains.

Aspect Extraction Domain Adaptation +1

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