May 18th, 2022 
Daniela Lopez de Luise
Tel Aviv, Israel, October 2022
https://sites.google.com/view/tie-eccv2022/home
in conjunction with ECCV 2022
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Understanding written communication through vision is a key aspect of human civilization and should also be an important capacity of intelligent agents aspiring to function in man-made environments. Interpreting written information in our environment is essential in order to perform most everyday tasks like making a purchase, using public transportation, finding a place in the city, getting an appointment, or checking whether a store is open or not, to mention just a few. As such, the analysis of written communication in images and videos has recently gained an increased interest, as well as significant progress in a variety of text based vision tasks. While in earlier years the main focus of this discipline was on OCR and the ability to read business documents, today this field contains various applications that require going beyond just text recognition, onto additionally reasoning over multiple modalities such as the structure and layout of documents.
Recent advances in this field have been a result of a multi-disciplinary perspective spanning not only computer vision, but also natural language processing, document and layout understanding, knowledge representation and reasoning, data mining, information retrieval, and more. The goal of this workshop is to raise awareness about the aforementioned topics in the broader computer vision community, and gather vision, NLP and other researchers together to drive a new wave of progress by cross pollinating more ideas between text/documents and non-vision related fields.
The workshop will be a hybrid, full-day event comprising invited talks, oral and poster presentations of submitted papers and a special challenge on Out of Vocabulary scene text understanding.
Keynote speakers
- Xiang Bai (Huazhong University)
- Tal Hassner (Meta AI)
- Aishwarya Agrawal (University of Montreal, DeepMind)
- Sharon Fogel (AWS AI Labs)
Topics of Interest
The workshop welcomes original work on any text-dependent computer vision application, such as:
- Scene text understanding
- Scene text VQA
- Image-text aware cross-modal retrieval
- Image-text for fine-grained classification
- Text in video
- Document VQA
- Document layout prediction
- Table detection
- Information extraction
Challenge on Out-of-Vocabulary Scene Text Understanding
A challenge on Out of Vocabulary Scene Text Understanding (OOV-ST) will be organised in the context of this workshop. The OOV-ST challenge aims to evaluate the ability of text extraction models to deal with out-of-vocabulary (OOV) words, that have NEVER been encountered in the training set of the most common Scene Text understanding datasets to date. The challenge is organised jointly by Amazon Research, Google Research, Meta AI, and the Computer Vision Center.
To participate to the OOV_ST Challenge, please join through the RRC Portal.
Important dates
Paper Submission Deadline: August 1, 2022
Notification to Authors: August 15, 2022
Workshop Camera Ready Due: August 22, 2022
Workshop Date: October 2022
Organisers
Ron Litman, AWS AI Labs
Aviad Aberdam, AWS AI Labs
Shai Mazor, AWS AI Labs
Hadar Averbuch-Elor, Cornell University
Dimosthenis Karatzas, Computer Vision Center / Autonomous University of Barcelona
R. Manmatha, AWS AI Labs
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