7 citations · 14 across the 7 of their papers we have counts for
7 papers
TDATR: Improving End-to-End Table Recognition via Table Detail-Aware Learning and Cell-Level Visual Alignment
Chunxia Qin, Chenyu Liu, Pengcheng Xia +4
Tables are pervasive in diverse documents, making table recognition (TR) a fundamental task in document analysis. Existing modular TR pipelines separately model table structure and…
Col-OLHTR: A Novel Framework for Multimodal Online Handwritten Text Recognition
Chenyu Liu, Jinshui Hu, Baocai Yin +4
Online Handwritten Text Recognition (OLHTR) has gained considerable attention for its diverse range of applications. Current approaches usually treat OLHTR as a sequence recognitio…
Exploring Part-Informed Visual-Language Learning for Person Re-Identification
Yin Lin, Yehansen Chen, Baocai Yin +4
Recently, visual-language learning (VLL) has shown great potential in enhancing visual-based person re-identification (ReID). Existing VLL-based ReID methods typically focus on ima…
The Multimodal Information based Speech Processing (MISP) 2022 Challenge: Audio-Visual Diarization and Recognition
Zhe Wang, Shilong Wu, Hang Chen +12
The Multi-modal Information based Speech Processing (MISP) challenge aims to extend the application of signal processing technology in specific scenarios by promoting the research…
SEMv2: Table Separation Line Detection Based on Instance Segmentation
Zhenrong Zhang, Pengfei Hu, Jiefeng Ma +6
Table structure recognition is an indispensable element for enabling machines to comprehend tables. Its primary purpose is to identify the internal structure of a table. Neverthele…
Lip-reading with Hierarchical Pyramidal Convolution and Self-Attention
Hang Chen, Jun Du, Yu Hu +3
In this paper, we propose a novel deep learning architecture to improving word-level lip-reading. On the one hand, we first introduce the multi-scale processing into the spatial fe…
Correlating Subword Articulation with Lip Shapes for Embedding Aware Audio-Visual Speech Enhancement
Hang Chen, Jun Du, Yu Hu +3
In this paper, we propose a visual embedding approach to improving embedding aware speech enhancement (EASE) by synchronizing visual lip frames at the phone and place of articulati…