activity
20182023
most citedRethinking Text Line Recognition Models

19 citations · 20 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL20231 cited

FormNetV2: Multimodal Graph Contrastive Learning for Form Document Information Extraction

Chen-Yu Lee, Chun-Liang Li, Hao Zhang +13

The recent advent of self-supervised pre-training techniques has led to a surge in the use of multimodal learning in form document understanding. However, existing approaches that…

cs.CL2021

ROPE: Reading Order Equivariant Positional Encoding for Graph-based Document Information Extraction

Chen-Yu Lee, Chun-Liang Li, Chu Wang +5

Natural reading orders of words are crucial for information extraction from form-like documents. Despite recent advances in Graph Convolutional Networks (GCNs) on modeling spatial…

cs.CV202119 cited

Rethinking Text Line Recognition Models

Daniel Hernandez Diaz, Siyang Qin, Reeve Ingle +2

In this paper, we study the problem of text line recognition. Unlike most approaches targeting specific domains such as scene-text or handwritten documents, we investigate the gene…

cs.CV2019

Towards Unconstrained End-to-End Text Spotting

Siyang Qin, Alessandro Bissacco, Michalis Raptis +2

We propose an end-to-end trainable network that can simultaneously detect and recognize text of arbitrary shape, making substantial progress on the open problem of reading scene te…

cs.CV2018

Automatic Semantic Content Removal by Learning to Neglect

Siyang Qin, Jiahui Wei, Roberto Manduchi

We introduce a new system for automatic image content removal and inpainting. Unlike traditional inpainting algorithms, which require advance knowledge of the region to be filled i…