activity
20202022
most citedIndustrial Scene Text Detection with Refined Feature-attentive Network

55 citations · 58 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2022★ 2 cited

Self-supervised Implicit Glyph Attention for Text Recognition

Tongkun Guan, Chaochen Gu, Jingzheng Tu +5

The attention mechanism has become the \emph{de facto} module in scene text recognition (STR) methods, due to its capability of extracting character-level representations. These me…

cs.CV2021★ 55 cited

Industrial Scene Text Detection with Refined Feature-attentive Network

Tongkun Guan, Chaochen Gu, Changsheng Lu +4

Detecting the marking characters of industrial metal parts remains challenging due to low visual contrast, uneven illumination, corroded character structures, and cluttered backgro…

cs.CV2021

CANS: Communication Limited Camera Network Self-Configuration for Intelligent Industrial Surveillance

Jingzheng Tu, Qimin Xu, Cailian Chen

Realtime and intelligent video surveillance via camera networks involve computation-intensive vision detection tasks with massive video data, which is crucial for safety in the edg…

cs.CV2020

Discriminative Feature Representation with Spatio-temporal Cues for Vehicle Re-identification

J. Tu, C. Chen, X. Huang +2

Vehicle re-identification (re-ID) aims to discover and match the target vehicles from a gallery image set taken by different cameras on a wide range of road networks. It is crucial…

cs.LG2020★ 1 cited

Attention-Aware Answers of the Crowd

Jingzheng Tu, Guoxian Yu, Jun Wang +2

Crowdsourcing is a relatively economic and efficient solution to collect annotations from the crowd through online platforms. Answers collected from workers with different expertis…