Rules & Registration

Guidelines for participating in the XLPSR Challenge

An Official Grand Challenge at IEEE ICIP 2026

Tampere, Finland • 13–17 September 2026

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Participation Overview

Eligibility
  • Open to researchers, students, and practitioners worldwide
  • Teams or individual participants allowed
  • Academic and industry participation welcomed
  • No participation fees required
Key Requirements
  • Registration through official challenge platform
  • Dataset license agreement
  • Submission of 2-page extended abstract
  • Reproducible code submission (Docker) for top selected participants
Critical Timeline Information

Review the challenge timeline carefully. Submissions must include both the super-resolution outputs AND the 2-page extended abstract by the final deadline.

Super-Resolution Approach

Single-Image SR (SISR)

Permitted ✓

  • Select any one frame from the 10-frame sequence
  • Apply standard single-image super-resolution
  • No requirement to use all frames
  • Frame selection strategy is part of your method
ŝ = 𝒢(I_{LR})

Multi-Image SR (MISR)

Permitted ✓

  • Use any subset or all 10 frames from the sequence
  • Leverage temporal information across frames
  • Frame fusion, alignment, or selection allowed
  • Any temporal aggregation strategy permitted
ŝ = 𝒢(I_{LR}^1, ..., I_{LR}^{10})

Method Freedom

There is no restriction on the number of frames used per sequence. Participants may:

  • Use exactly 1 frame (any frame of their choice)
  • Use all 10 frames
  • Use any subset between 2-9 frames
  • Dynamically select frames per sequence
  • Combine multiple frames into a single enhanced image
Evaluation:
Only the final predicted license plate text is scored. The method is free.

This rule applies to ALL phases: development, public validation, and blind test set evaluation.

Challenge Rules & Guidelines

Evaluation & Scoring

  • Primary Metric: Character Error Rate (CER) with custom scoring rules
  • Format Requirement: Predictions must match French license plate format: old license plates 123-AAA-12 or 1234-AA-12 (3 or 4 degits, 2 or 3 letters, 2 degits), and new license late AA-123-AA (2 letters, 3 digits, 2 letters).
  • Scoring System:
    • Correct character at correct position: +2 points
    • No prediction for character: 0 points
    • Wrong character (hallucination): -1 point
  • Maximum Score: 14 points (7 characters × 2 points)
  • Minimum Score: -7 points (7 characters × -1 point)

Submission Requirements

  • Final Submission: Must include both:
    • Super-resolution outputs for all test sequences
    • 2-page extended abstract in IEEE conference format
  • Output Format: CSV file with columns: sequence_id and predicted_lp
  • Abstract Format: PDF following IEEE ICIP 2026 template guidelines
  • Model Submission: Top-performing teams must submit reproducible Docker containers on invitation. See the Docker preparation and submission guidelines.

Prohibited Practices

  • Manual annotation or manipulation of test data
  • Using undisclosed external data
  • Multiple accounts or team splitting
  • Attempting to reverse-engineer the blind test set
  • Any form of cheating or unfair advantage

Permitted Practices

  • Use of any publicly available data for training
  • Pre-trained models and transfer learning
  • Data augmentation and synthetic data generation
  • Ensemble methods and model combination
  • External tools for preprocessing

Recommended Public Datasets

Participants are encouraged to use additional data. Below are some publicly available license plate datasets suitable for pre‑training or data augmentation. Please respect each dataset's license terms and citation requirements.

  • UFPR-SR-Plates – GitHub
    100k images with paired low/high-resolution sequences for super‑resolution. Real‑world surveillance conditions.
  • Realistic License Plate Restoration and Recognition (RLPR) – Mendeley Data
    31‑frame low‑quality sequences paired with high‑quality targets for multi‑frame restoration.
  • Chinese City Parking Dataset (CCPD) – GitHub
    Over 250k images with subsets for blur, tilt, weather, distance. Widely used for detection/recognition.
  • Ukrainian License Plate Dataset (Synthetic) – Zenodo
    10k synthetic LP images generated with diffusion models.
  • European License Plates (ELP 1.0) – GitHub
    Covers 20 European countries with diverse plate formats.

Some datasets may require registration or license acceptance.

2-Page Extended Abstract Requirements

The extended abstract is mandatory for all final submissions and must include:

  • Complete description of the proposed super-resolution method
  • Architecture details and training methodology
  • List of all external data used for training
  • Experimental results on the validation set
  • References to related work
  • Compliance with IEEE ICIP 2026 formatting guidelines

Registration Process

1
Platform Access

Receive credentials for CodaBench challenge platform and dataset download instructions.

2
Sign License Agreement

Accept the IMPROVED dataset terms of use and license agreement.

3
Complete Registration Form

Fill out the official registration form with team member details and contact information.

4
Begin Development

Access the development dataset and start building your super-resolution solution.

Ready to Participate?

Complete your registration to access the development dataset and join the XLPSR Challenge leaderboard.

Register Now View Dataset Details

Registration approval typically within 24-48 hours.
Questions? Review the contact page for support.