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20182023
most citedGPT-NER: Named Entity Recognition via Large Language Models

146 citations · 437 across the 28 of their papers we have counts for

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Showing 2021 · cs.CVShow all

6 papers · 2 filters

cs.CV2021★ 5 cited

Memory Regulation and Alignment toward Generalizer RGB-Infrared Person

Feng Chen, Fei Wu, Qi Wu +1

The domain shift, coming from unneglectable modality gap and non-overlapped identity classes between training and test sets, is a major issue of RGB-Infrared person re-identificati…

cs.CV2021

VSR: A Unified Framework for Document Layout Analysis combining Vision, Semantics and Relations

Peng Zhang, Can Li, Liang Qiao +4

Document layout analysis is crucial for understanding document structures. On this task, vision and semantics of documents, and relations between layout components contribute to th…

cs.CV2021

Modeling High-order Interactions across Multi-interests for Micro-video Recommendation

Dong Yao, Shengyu Zhang, Zhou Zhao +4

Personalized recommendation system has become pervasive in various video platform. Many effective methods have been proposed, but most of them didn't capture the user's multi-level…

cs.CV2021

Reciprocal Feature Learning via Explicit and Implicit Tasks in Scene Text Recognition

Hui Jiang, Yunlu Xu, Zhanzhan Cheng +5

Text recognition is a popular topic for its broad applications. In this work, we excavate the implicit task, character counting within the traditional text recognition, without add…

cs.CV2021

LGPMA: Complicated Table Structure Recognition with Local and Global Pyramid Mask Alignment

Liang Qiao, Zaisheng Li, Zhanzhan Cheng +6

Table structure recognition is a challenging task due to the various structures and complicated cell spanning relations. Previous methods handled the problem starting from elements…

cs.CV2021

Leaning Compact and Representative Features for Cross-Modality Person Re-Identification

Guangwei Gao, Hao Shao, Fei Wu +2

This paper pays close attention to the cross-modality visible-infrared person re-identification (VI Re-ID) task, which aims to match pedestrian samples between visible and infrared…