most citedVideo Cloze Procedure for Self-Supervised Spatio-Temporal Learning

24 citations · 65 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV202017 cited

Two-Level Residual Distillation based Triple Network for Incremental Object Detection

Dongbao Yang, Yu Zhou, Dayan Wu +3

Modern object detection methods based on convolutional neural network suffer from severe catastrophic forgetting in learning new classes without original data. Due to time consumpt…

cs.CV20204 cited

Self-Training for Domain Adaptive Scene Text Detection

Yudi Chen, Wei Wang, Yu Zhou +3

Though deep learning based scene text detection has achieved great progress, well-trained detectors suffer from severe performance degradation for different domains. In general, a…

cs.CV202020 cited

SEED: Semantics Enhanced Encoder-Decoder Framework for Scene Text Recognition

Zhi Qiao, Yu Zhou, Dongbao Yang +2

Scene text recognition is a hot research topic in computer vision. Recently, many recognition methods based on the encoder-decoder framework have been proposed, and they can handle…

cs.CV202024 cited

Video Cloze Procedure for Self-Supervised Spatio-Temporal Learning

Dezhao Luo, Chang Liu, Yu Zhou +4

We propose a novel self-supervised method, referred to as Video Cloze Procedure (VCP), to learn rich spatial-temporal representations. VCP first generates "blanks" by withholding v…

cs.CV2019

Curved Text Detection in Natural Scene Images with Semi- and Weakly-Supervised Learning

Xugong Qin, Yu Zhou, Dongbao Yang +1

Detecting curved text in the wild is very challenging. Recently, most state-of-the-art methods are segmentation based and require pixel-level annotations. We propose a novel scheme…