Knowledge distillation learns a lightweight student model that mimics a
...
Expandable networks have demonstrated their advantages in dealing with
c...
In the SSLAD-Track 3B challenge on continual learning, we propose the me...
Few-shot learning (FSL) aims to learn models that generalize to novel cl...
Text recognition is a popular topic for its broad applications. In this ...
Recently end-to-end scene text spotting has become a popular research to...
Since real-world ubiquitous documents (e.g., invoices, tickets, resumes ...
Arbitrary text appearance poses a great challenge in scene text recognit...
Recurrent neural network (RNN) has been widely studied in sequence learn...
Many approaches have recently been proposed to detect irregular scene te...
Temporal action localization is an important yet challenging research to...
This paper proposes a segregated temporal assembly recurrent (STAR) netw...
Scene text recognition has been a hot research topic in computer vision ...