Final CFP: ICCV 2019 Workshop and Challenge on Real-World Recognition from Low-Quality Images and Videos (RLQ2019)

[yuqian zhou]

ICCV 2019 Workshop and Challenge on Real-World Recognition from Low-Quality Images and Videos (RLQ2019)
Seoul, South Korea, 27 Oct 2019
http://www.forlq.org/

Introduction:
What is the current state-of-the-art for recognition and detection algorithms in non-ideal visual environments? We are organizing the RLQ workshop and challenge in ICCV 2019. RLQ 2019 consists of challenge, keynote speech, paper presentation, poster session, special session on privacy and ethics of visual recognition, and a panel discussion from the invited speakers.

Important Dates
Paper submission deadline: Aug. 1, 2019 (11:59PM PST)
Notification to authors: Aug. 20, 2019 (11:59PM PST)
Camera-ready deadline: Aug. 28, 2019 (11:59PM PST)
Workshop day: Oct. 27, 2019 (Full day)

[Challenge Track] by 30 Aug. 2019
• Low-quality Image Recognition Challenge organized by QMUL
https://evalai.cloudcv.org/web/challenges/challenge-page/392/overview


Call for Papers
Original high-quality contributions are solicited on the following topics:

[Paper Track]
• Robust recognition and detection from low-resolution image/video
• Robust recognition and detection from video with motion blur
• Robust recognition and detection from highly noisy image/video
• Robust recognition and detection from other unconstrained environment conditions
• Artificial Degradations
• Low-resolution image/video enhancement, especially for recognition purpose
• Image/video denoising and deblurring, especially for recognition purpose
• Restoration and enhancement of other common degradations, such as low-illumination, inclement weathers, etc., especially for recognition purpose
• Novel methods and metrics for image restoration and enhancement algorithms, especially for recognition purpose
• Surveys of algorithms and applications with LQ inputs in computer vision
• Psychological and cognitive science research with proper data processing and enhancement
• Novel calibration and registration methods on gaze or object images etc. for recognition or detection purpose.
• Novel imperfect low-quality data mining, cleaning, and processing methods for training a recognition system.
• Other novel applications that robustly handle computer vision tasks with LQ inputs
• Special Topic: Legal, privacy, and ethics in recognition

[Abstract Track]
We solicit “positioning” write-ups, in the form of short non-archival abstracts. They shall address important issues that may generate a lasting impact for next 5-year research in the field of recognition in low-quality visual data. Examples may include but are not limited to,
• Proposing novel technical solutions: preliminary works and “half-baked” results are welcome
• Identifying grand challenges that are traditionally overlooked or under-explored
• Discussing rising applications where recognition from low-quality visual data might have been a critical bottleneck
• Raising new research questions that may be motivated by emerging applications
• New datasets, new benchmark efforts, and/or new evaluation strategies
• Integration of low-quality visual recognition into other research topics


Authors Guidelines
- Each submitted full-paper must be no longer than eight pages, excluding references. Please refer to the ICCV-2019 author submissions guidelines regarding formatting, templates, and policies. The submissions will go through a double-blind review process by the program committee. Selected papers will be published in ICCV IEEE/CVF Workshop proceedings.
- Each submitted abstract must be no longer than two pages, excluding references, in the format of ICCV-2019. The non-blind submissions will be also reviewed by the program committee, on a selective and competitive basis. The accepted abstracts will appear on the website. The workshop organizers will lead a collective positioning paper, targeted at a top-tier journal such as TPAMI or IJCV. Those whose abstracts are selected will be invited as co-authors of this paper (the author order will be alphabetical).
- We will set up best paper awards for the full papers.


Invited Speakers
Rama Chellappa Prof. UMD
Matthew Turk, Prof. UCSB
Gang Hua, VP&Chief Scientist, Wormpex AI Research
Jeffrey Cohn, Prof. Pitt&CMU
Manmohan Chandraker, Prof. UCSD
Xiaoming Liu, Prof. MSU

Contact:
General Inquiry: cha...@forlq.org
Challenge Inquiry: chal...@forlq.org
Website: www.forlq.org

**It would be highly appreciated if you could disseminate this CFP among your colleagues**