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FOR-LQ 2018 : IEEE FG Workshop on Real-World Face and Object Recognition from Low-Quality Images (FOR-LQ)

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Link: http://staff.ustc.edu.cn/~dongeliu/forlq2018/index.html
 
When May 15, 2018 - May 15, 2018
Where Xi'an, China
Submission Deadline Jan 28, 2018
Notification Due Feb 25, 2018
Final Version Due Mar 4, 2018
Categories    computer vision   machine learning   deep learning   image processing
 

Call For Papers


FOR-LQ 2018

In many emerging applications such as video surveillance, robotics and autonomous driving, the performances of visual sensing and analytics are largely jeopardized by low-quality visual data acquired from complex unconstrained environments, suffering from various types of degradations such as low resolution, noise, occlusion and motion blur.

This workshop (FOR-LQ 2018) will provide an integrated forum for researchers to review the recent progress of robust face and object recognition from low-quality visual data. We embrace the most advanced deep learning systems, meanwhile being open to classical physically grounded models and feature engineering, as well as any well-motivated combination of the two streams.


TOPICS

- Face and object recognition, especially from low-resolution image/video, video with motion blurs, highly noisy image/video, and/or other unconstrained environment conditions
- Recognition-oriented image/video super-resolution, image/video denoising and deblurring, and/or restoration and enhancement of other degradations such as low-illumination, inclement weathers, etc.
- Applications that robustly handle computer vision tasks with low-quality inputs
- Evaluating methods and metrics for image restoration and enhancement, especially for recognition purpose


SUBMISSIONS

Short paper: 4 pages + 1 page for references
IEEE conference paper template (anonymous submission)
More information:
https://fg2018.cse.sc.edu/submissions.html

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