1st Place Solution to ECCV 2022 Challenge on Out of Vocabulary Scene Text Understanding: End-to-End Recognition of Out of Vocabulary Words
This addresses the challenge of extracting unknown words from natural scenes, which is incremental as it builds on existing scene text recognition methods.
The paper tackled the problem of recognizing out-of-vocabulary words in scene text images, achieving a first-place result with a 28.59% h-mean score in the ECCV 2022 challenge.
Scene text recognition has attracted increasing interest in recent years due to its wide range of applications in multilingual translation, autonomous driving, etc. In this report, we describe our solution to the Out of Vocabulary Scene Text Understanding (OOV-ST) Challenge, which aims to extract out-of-vocabulary (OOV) words from natural scene images. Our oCLIP-based model achieves 28.59\% in h-mean which ranks 1st in end-to-end OOV word recognition track of OOV Challenge in ECCV2022 TiE Workshop.