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…
Binary-Gaussian: Compact and Progressive Representation for 3D Gaussian Segmentation
An Yang, Chenyu Liu, Jun Du +6
3D Gaussian Splatting (3D-GS) has emerged as an efficient 3D representation and a promising foundation for semantic tasks like segmentation. However, existing 3D-GS-based segmentat…
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…
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…
RFL: Simplifying Chemical Structure Recognition with Ring-Free Language
Qikai Chang, Mingjun Chen, Changpeng Pi +6
The primary objective of Optical Chemical Structure Recognition is to identify chemical structure images into corresponding markup sequences. However, the complex two-dimensional s…
Hi-SAM: Marrying Segment Anything Model for Hierarchical Text Segmentation
Maoyuan Ye, Jing Zhang, Juhua Liu +5
The Segment Anything Model (SAM), a profound vision foundation model pretrained on a large-scale dataset, breaks the boundaries of general segmentation and sparks various downstrea…