What are the possible future research directions for OCR researchers (when we achieve almost 100% accuracy)? This slide is for a short opening talk to stimulate audiences. Actually, young researchers on OCR or other document processing-related research need to think about their "NEXT".

1. 1
Beyond 100%
ICDAR Special Workshop on Future DAR
Seiichi Uchida, Kyushu University, Japan

2. 2
Near-human performance has been
achieved by big data and neural networks
machine printed
handwritten
designed fonts
95.49%
99.79%
99.99%
[Zhou+, CVPR2017]
Scene text detection
Scene text recognition
CRNN [Shi+, TPAMI, 2017]
F value=0.8 on
ICDAR2015 Incidental scene text
89.6% word recog. rate
on ICDAR2013

3. 3
Now we can imagine
what we can do in the world
Beyond 100%

4. 4
Beyond 100% = Computer can detect, read,
and collect all text information perfectly
Texts on notebook
Texts on object label
Texts on digital display
Texts on book page
Texts on signboard
Texts on poster / ad
So, what do you want to do
with the perfect recognition results?

5. 5
Poor recognition results
In fact, our real goal should NOT be
perfect recognition results
Real goals
Ultimate application
by using perfect
recognition results
Scientific discovery
by analyzing perfect
recognition results
Perfect recognition results
Tentative goal

6. 6
What will you do
in the world beyond 100%?
Ultimate application
 Education
 “Total-recall” for perfect
information search
 Welfare
 Alarm, translation,
information complement
 “Life log”-related apps
 Summary, log compression,
captioning, question
answering, behavior
prediction, reminder
Scientific discovery
 With social science
 Interaction between scene
text and human
 Text statistics
 With design science
 Font shape and impression
 Discovering typographic
knowledge
 With humanities
 Historical knowledge
 Semiology

7. 7
The last message...
... and please do NOT become an accuracist,
parameter-tuner, and libraholic!