Overview
The Extreme In-The-Wild License Plate Super-Resolution (XLPSR) Challenge establishes a benchmark for reconstructing readable French license plates from low-resolution, degraded video frames. Participants must develop super-resolution models that address authentic degradations like motion blur, compression artifacts, and noise, specific to real-world acquisition scenarios.
The core requirement is the accurate, hallucination-free recovery of the alphanumeric characters and the standardized format of French plates, ensuring outputs are reliable for downstream Optical Character Recognition (OCR). Solutions may process frames independently or exploit temporal coherence in video. The use of auxiliary modules for denoising, deblurring, or dehazing is permitted within the model pipeline.
Significance
Pushing SR into extreme regimes: Unlike common SR challenges (NTIRE, AIM), XLPSR addresses magnification under severe real-world degradations, motivating attention, diffusion-based SR, and degradation-aware pipelines.
High-impact application: Readable plates are critical for ITS, security, and forensics. The primary automated metric prioritizes functional correctness over purely perceptual quality.
Hallucination-free generation: OCR-based evaluation encourages fidelity and avoids plausible but incorrect characters, aligning with reliability in generative models.
Participate in the Challenge
The XLPSR Challenge is now open for registration as part of IEEE ICIP 2026. To join, participants must complete a one-time registration process which grants access to the dataset and the submission platform.
📋 Step 1: Official Registration
All participants must first register via the official form. This process includes signing the dataset license agreement and creating an account on our evaluation platform, CodaBench.
👉 Click here to access the XLPSR Challenge Registration Form
⏳ Timeline & Next Steps
The final competition timeline is being finalized with the IEEE ICIP 2026 organizers. Key milestones, including the dataset release and submission deadlines, will be announced here and on the official conference website.
How to prepare after registering:
- Review the dataset details and proposed timeline structure.
- Familiarize yourself with the official rules & evaluation protocol.
- Upon approval of your registration, you will receive access instructions for the dataset and CodaBench.