method: LOGO2024-05-30

Authors: Hongen Liu, Yi Liu, Di Sun, Jiahao Wang, Gang Pan

Affiliation: College of Intelligence and Computing, Tianjin University; Baidu Inc. ;Tianjin University of Science and Technology

Description: We propose a Language Collaboration and Glyph Perception Model, termed LOGO to enhance the performance of conventional text spotters through the integration of a synergy module. To achieve this goal, a language synergy classifier (LSC) is designed to explicitly discern text instances from background noise in the recognition stage. Besides, the glyph supervision and visual position mixture module are proposed to enhance the recognition accuracy of noisy text regions, and acquire more discriminative tracking features, respectively.

Authors: Liu Hongen

Affiliation: Tianjin Univeristy

Email: y2998388548@163.com

Description: We use the ppyoloe-r which proposed by Baidu and sort algorithm to solve the video text tracking for dense and small text problem

Ranking Table

Description Paper Source Code
DateMethodMOTAMOTPIDF1Mostly MatchedPartially MatchedMostly Lost
2024-05-30LOGO51.36%77.57%65.70%574321004734
2023-03-20Video Text Tracking for Dense and Small Text Based on PP-YOLOE-R and Sort Algorithm36.87%79.24%48.99%212336256829

Ranking Graphic