PIMNet: A Parallel, Iterative and Mimicking Network for Scene Text Recognition
Comments Accepted by ACM MM 2021
期刊&会议
ACM International Conference on Multimedia · 会议 · Multimedia
Comments Accepted by ACM MM 2021
Comments 10 pages, 6 figures, Accepted by ACM MM 2021
Comments Accepted by ACM MM 2021
Comments 2 Figures, 2 Tables, Accepted for publication at the 1st Workshop on Synthetic Multimedia - Audiovisual Deepfake Generation and Detection (ADGD '21) at ACM MM 2021
Comments Accepted to ACM Multimedia (ACMMM) 2021
Comments Accepted to ACM MM 2021
Comments 10 pages, 5 figures. Accepted to International Workshop on Adversarial Learning for Multimedia, ACM Multimedia 2021
Comments ACMMM 2021
Comments Accepted by ACM MM'21 (oral presentation)
Comments To appear at ACM Multimedia 2021 (8 pages, 5 figures)
Comments 4 pages; 2 figures; ACM MM 2021 workshop; Tencent Advertising Algorithm Competition ACM Multimedia 2021 Grand Challenge
Comments Accepted to ACM MM 2021
Comments Accepted by ACM MM'21 (oral)
Comments Accepted to ACM Multimedia 2021 as Oral
Comments Accepted at ACM Multimedia (ACMMM) 2021
Comments Accepted as Oral by ACMMM 2021
Comments Accepted by ACM Multimedia 2021
Comments ACM MM 2021
Journal ref Proceedings of the 29th ACM International Conference on Multimedia (MM '21), October 20--24, 2021, Virtual Event, China
Comments ACM MM 2020
Comments ACMMM 2021 (Oral). Code available at https://github.com/yikaiw/EIP. arXiv admin note: substantial text overlap with arXiv:2011.11528
Comments Accepted at ACM Multimedia (ACMMM) 2021 . Code, pretrained models and interactive visualizations can be viewed at our project page https://deepcount.iiit.ac.in/
Journal ref ACMMM 2021
Comments 1st of Video Relation Understanding (VRU) Grand Challenge in ACM Multimedia 2021
Comments ACM MM Oral paper
Comments Accepted to ACM MM 2021 (oral)
Comments Accepted by ACM Multimedia Open Source Software Competition
Comments Accepted by 2021 ACMMM Open Source Software Competition. Source code: https://github.com/YehLi/xmodaler
Comments 9 pages, 6 figures, received by ACM MM'21
Comments Accepted at ACM Multimedia 2021. Code available at https://github.com/MILVLG/rosita