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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…
Cross-modulated Attention Transformer for RGBT Tracking
Yun Xiao, Jiacong Zhao, Andong Lu +4
Existing Transformer-based RGBT trackers achieve remarkable performance benefits by leveraging self-attention to extract uni-modal features and cross-attention to enhance multi-mod…
1DFormer: a Transformer Architecture Learning 1D Landmark Representations for Facial Landmark Tracking
Shi Yin, Shijie Huan, Shangfei Wang +5
Recently, heatmap regression methods based on 1D landmark representations have shown prominent performance on locating facial landmarks. However, previous methods ignored to make d…
Weakly Supervised Scene Text Generation for Low-resource Languages
Yangchen Xie, Xinyuan Chen, Hongjian Zhan +4
A large number of annotated training images is crucial for training successful scene text recognition models. However, collecting sufficient datasets can be a labor-intensive and c…
VGTS: Visually Guided Text Spotting for Novel Categories in Historical Manuscripts
Wenbo Hu, Hongjian Zhan, Xinchen Ma +3
In the field of historical manuscript research, scholars frequently encounter novel symbols in ancient texts, investing considerable effort in their identification and documentatio…