720 citations · 727 across the 8 of their papers we have counts for
8 papers
Progressive Evidence Refinement for Open-domain Multimodal Retrieval Question Answering
Shuwen Yang, Anran Wu, Xingjiao Wu +4
Pre-trained multimodal models have achieved significant success in retrieval-based question answering. However, current multimodal retrieval question-answering models face two main…
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…
Progressive Scene Text Erasing with Self-Supervision
Xiangcheng Du, Zhao Zhou, Yingbin Zheng +3
Scene text erasing seeks to erase text contents from scene images and current state-of-the-art text erasing models are trained on large-scale synthetic data. Although data syntheti…
Cross-Domain Document Layout Analysis Using Document Style Guide
Xingjiao Wu, Luwei Xiao, Xiangcheng Du +5
The document layout analysis (DLA) aims to decompose document images into high-level semantic areas (i.e., figures, tables, texts, and background). Creating a DLA framework with st…
Document Layout Analysis with Aesthetic-Guided Image Augmentation
Tianlong Ma, Xingjiao Wu, Xin Li +4
Document layout analysis (DLA) plays an important role in information extraction and document understanding. At present, document layout analysis has reached a milestone achievemen…
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…
A Survey of Human-in-the-loop for Machine Learning
Xingjiao Wu, Luwei Xiao, Yixuan Sun +3
Human-in-the-loop aims to train an accurate prediction model with minimum cost by integrating human knowledge and experience. Humans can provide training data for machine learning…
Scene Text Recognition with Temporal Convolutional Encoder
Xiangcheng Du, Tianlong Ma, Yingbin Zheng +3
Texts from scene images typically consist of several characters and exhibit a characteristic sequence structure. Existing methods capture the structure with the sequence-to-sequenc…