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RLQ-TOD 2020 : 1st Tiny Object Detection (TOD) Challenge Real-world Recognition from Low-quality Inputs (RLQ)

Glasgow, UK
Event Date: Aug 28, 2020 - Aug 28, 2020
Submission Deadline: Jun 25, 2020
Notification of Acceptance: Jul 10, 2020
Camera Ready Version Due : Jul 17, 2020

About

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. We will solicit papers from but not limited to the following topics:

  • Robust recognition and detection from images with low-resolution, high noise, or other real-world unconstrained environment conditions and artificial degradation;
  • Robust recognition and detection from videos with motion blur, low-resolution, high noise, or other real-world unconstrained environment conditions and artificial degradation;
  • Low-quality (LQ) image and video enhancement including denoising, de-blurring, super-resolution etc., especially for recognition purpose;
  • Human parsing, activity analysis, and action recognition at long distance; Crowd counting;
  • Surveys of algorithms and applications with LQ inputs;
  • Datasets for low-resolution vision and/or analyses of existing methods;
  • Low-quality data pre-processing methods for inter-disciplinary research like Psychology, cognitive science, and human computer interaction;
  • Legal, privacy and ethics discussions and methods in recognition research;

Call For Paper

Submitted paper will go through a double-blind peer-reviewed process, and the accepted papers will appear in the ECCV Workshop Proceedings. All submissions should follow the requirement of ECCV main conference in terms of format and length.

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