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

[yuqian zhou]

CCV 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/  <http://www.forlq.com/>

*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)

*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

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

*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.

*Organizers*
Yuqian Zhou*, Ph.D. Student, UIUC
Yunchao Wei*, Postdoc Researcher & Project Scientist, UIUC
Zhangyang Wang, Assistant Professor, TAMU
Jiaying Liu, Associate Professor, PKU
Ding Liu, Research Scientist, Bytedance Inc
Shaogang Gong, Professor, Queen Mary University of London
Jeffrey Cohn, Professor, Unversity of Pittsburgh and CMU
Nicu Sebe, Professor, University of Trento
Honghui Shi, Research Stall Member, IBM Research
Thomas S. Huang, Research Professor, UIUC, USA

*Challenge Committee*
Zhiyi Cheng, Qi Dong Ph.D QMUL

*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: chairs at forlq.org
Challenge Inquiry: challenge at forlq.org
*Website:* www.forlq.org

**It would be highly appreciated if you could disseminate this CFP among
your colleagues**
--------------------------------------------------------------------------------------------------
Ph.D Candidate of ECE Department, Beckman Institute
*University of Illinois at Urbana-Champaign (UIUC) *
Master of Philosophy of ECE Department
*The Hong Kong University of Science and Technology*
Phone: +1 (217) 607 3041
Email: zhouyuqian133 at gmail.com, yuqian2 at illinois.edu, yzhouas at ust.hk
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