VTLayout: A Multi-Modal Approach for Video Text Layout
Author:
Affiliation:
1. Tencent PCG, Beijing, China
2. University of Science and Technology of China, Beijing, China
3. Tencent PCG, Shenzhen, China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3581783.3611870
Reference45 articles.
1. Ali Furkan Biten , Ron Litman , Yusheng Xie , Srikar Appalaraju , and R. Manmatha . 2021 . LaTr: Layout-Aware Transformer for Scene-Text VQA. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) ( 2021 ), 16527--16537. Ali Furkan Biten, Ron Litman, Yusheng Xie, Srikar Appalaraju, and R. Manmatha. 2021. LaTr: Layout-Aware Transformer for Scene-Text VQA. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2021), 16527--16537.
2. Spatiotemporal text localization for videos
3. You Only Recognize Once
4. FREE: A Fast and Robust End-to-End Video Text Spotter
5. ICDAR 2021 Competition on Scene Video Text Spotting
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