9 citations · 16 across the 5 of their papers we have counts for
5 papers
OmniTabBench: Mapping the Empirical Frontiers of GBDTs, Neural Networks, and Foundation Models for Tabular Data at Scale
Dihong Jiang, Ruoqi Cao, Zhiyuan Dang +8
While traditional tree-based ensemble methods have long dominated tabular tasks, deep neural networks and emerging foundation models have challenged this primacy, yet no consensus…
Look Closer to Supervise Better: One-Shot Font Generation via Component-Based Discriminator
Yuxin Kong, Canjie Luo, Weihong Ma +4
Automatic font generation remains a challenging research issue due to the large amounts of characters with complicated structures. Typically, only a few samples can serve as the st…
SwinTextSpotter: Scene Text Spotting via Better Synergy between Text Detection and Text Recognition
Mingxin Huang, Yuliang Liu, Zhenghao Peng +6
End-to-end scene text spotting has attracted great attention in recent years due to the success of excavating the intrinsic synergy of the scene text detection and recognition. How…
From Two to One: A New Scene Text Recognizer with Visual Language Modeling Network
Yuxin Wang, Hongtao Xie, Shancheng Fang +3
In this paper, we abandon the dominant complex language model and rethink the linguistic learning process in the scene text recognition. Different from previous methods considering…
Scene Text Retrieval via Joint Text Detection and Similarity Learning
Hao Wang, Xiang Bai, Mingkun Yang +3
Scene text retrieval aims to localize and search all text instances from an image gallery, which are the same or similar to a given query text. Such a task is usually realized by m…