  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.
