Awesome

IMCDB

A dataset of digitized comic storybooks in the English language with ground truth annotations for each panel in pages and ground truth text files for each narration box and speech balloon within a panel. Additionally, ground truth binary masks of speech balloons and narration box for each page.

Publication Details

This paper was published in ICDAR 2021

Citation Details

Plain Text

Gupta, V., Detani, V., Khokar, V., Chattopadhyay, C. (2021). C2VNet: A Deep Learning Framework Towards Comic Strip to Audio-Visual Scene Synthesis. In: Lladós, J., Lopresti, D., Uchida, S. (eds) Document Analysis and Recognition – ICDAR 2021. ICDAR 2021. Lecture Notes in Computer Science(), vol 12822. Springer, Cham. https://doi.org/10.1007/978-3-030-86331-9_11

Bibtex

@inproceedings{DBLP:conf/icdar/GuptaDKC21,
  author    = {Vaibhavi Gupta and
               Vinay Detani and
               Vivek Khokar and
               Chiranjoy Chattopadhyay},
  editor    = {Josep Llad{\'{o}}s and
               Daniel Lopresti and
               Seiichi Uchida},
  title     = {C2VNet: {A} Deep Learning Framework Towards Comic Strip to Audio-Visual
               Scene Synthesis},
  booktitle = {16th International Conference on Document Analysis and Recognition,
               {ICDAR} 2021, Lausanne, Switzerland, September 5-10, 2021, Proceedings,
               Part {II}},
  series    = {Lecture Notes in Computer Science},
  volume    = {12822},
  pages     = {160--175},
  publisher = {Springer},
  year      = {2021},
  url       = {https://doi.org/10.1007/978-3-030-86331-9\_11},
  doi       = {10.1007/978-3-030-86331-9\_11},
  timestamp = {Thu, 16 Sep 2021 18:08:10 +0200},
  biburl    = {https://dblp.org/rec/conf/icdar/GuptaDKC21.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}