activity
20182022
most citedEnhancing Event-Level Sentiment Analysis with Structured Arguments

5 citations · 8 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV20222 cited

Homogeneous Multi-modal Feature Fusion and Interaction for 3D Object Detection

Xin Li, Botian Shi, Yuenan Hou +4

Multi-modal 3D object detection has been an active research topic in autonomous driving. Nevertheless, it is non-trivial to explore the cross-modal feature fusion between sparse 3D…

cs.CL2022

A Knowledge-Enhanced Adversarial Model for Cross-lingual Structured Sentiment Analysis

Qi Zhang, Jie Zhou, Qin Chen +3

Structured sentiment analysis, which aims to extract the complex semantic structures such as holders, expressions, targets, and polarities, has obtained widespread attention from b…

cs.CL20225 cited

Enhancing Event-Level Sentiment Analysis with Structured Arguments

Qi Zhang, Jie Zhou, Qin Chen +2

Previous studies about event-level sentiment analysis (SA) usually model the event as a topic, a category or target terms, while the structured arguments (e.g., subject, object, ti…

cs.CL2022

Multi-channel Attentive Graph Convolutional Network With Sentiment Fusion For Multimodal Sentiment Analysis

Luwei Xiao, Xingjiao Wu, Wen Wu +2

Nowadays, with the explosive growth of multimodal reviews on social media platforms, multimodal sentiment analysis has recently gained popularity because of its high relevance to t…

cs.CV20211 cited

Human-In-The-Loop Document Layout Analysis

Xingjiao Wu, Tianlong Ma, Xin Li +2

Document layout analysis (DLA) aims to divide a document image into different types of regions. DLA plays an important role in the document content understanding and information ex…

cs.CV2018

Attention Incorporate Network: A network can adapt various data size

Liangbo He, Hao Sun

In traditional neural networks for image processing, the inputs of the neural networks should be the same size such as 224*224*3. But how can we train the neural net model with dif…