MARS by MARSAIL

🚀 About MARS

MARS is a state-of-the-art deep learning model for car damage instance segmentation. By leveraging sequential quadtree attention, it surpasses existing methods (Mask R-CNN, PointRend, Mask Transfiner) with notable maskAP gains.

+1.3 maskAP improvement (R50-FPN)
+2.3 maskAP improvement (R101-FPN) on Thai car-damage dataset

Presented at ICIAP 2023, Udine, Italy 🇮🇹

🏁 About MARSAIL Lab

MARSAIL (Motor AI Recognition Solution Artificial Intelligence Laboratory) is dedicated to pioneering research at the intersection of computer vision, transformers, and automotive AI.

Our mission is to revolutionize the automotive insurance and repair industries through AI-driven automation, delivering breakthroughs in segmentation, localization, and decision intelligence.

✨ Visual Results

MARS delivers superior segmentation accuracy:

📚 MARSAIL Research Highlights (2023–2025)

At the forefront of automotive AI innovation, all pioneering research at MARSAIL is led by Dr. Kao (Teerapong Panboonyuen), our visionary Head of AI Laboratory. Under his guidance, these groundbreaking works have advanced the fields of car damage evaluation, segmentation, and document understanding in the automotive domain.

🚗 ALBERT: Advanced Transformers for Automotive Damage Evaluation (Teacher Model)

A pioneering transformer-based architecture designed to act as a teacher model for vehicle damage evaluation tasks. ALBERT provides rich contextual embeddings and accurate localization signals that guide downstream student models. [Read on arXiv]

@article{panboonyuen2025albert,
  title={ALBERT: Advanced Localization and Bidirectional Encoder Representations from Transformers for Automotive Damage Evaluation},
  author={Panboonyuen, Teerapong},
  journal={arXiv preprint arXiv:2506.10524},
  year={2025}
}

🧠 SLICK: Knowledge-Enhanced Car Damage Segmentation (Student Model)

Trained under the supervision of ALBERT, SLICK leverages knowledge distillation and selective localization to excel in fine-grained car damage segmentation tasks — a student model optimized for real-world insurance workflows. [Read on arXiv]

@article{panboonyuen2025slick,
  title={SLICK: Selective Localization and Instance Calibration for Knowledge-Enhanced Car Damage Segmentation in Automotive Insurance},
  author={Panboonyuen, Teerapong},
  journal={arXiv preprint arXiv:2506.10528},
  year={2025}
}

🔍 DOTA: OCR with Retrieval-Augmented Generation for Automotive Services

Combines deformable attention mechanisms and Retrieval-Augmented Generation (RAG) for robust end-to-end document understanding in the automotive industry. [Read on arXiv]

@inproceedings{marsail2025dota,
  title={DOTA: Deformable Optimized Transformer Architecture for End-to-End Text Recognition with Retrieval-Augmented Generation},
  author={Panboonyuen, Teerapong as co-author and lead researcher},
  booktitle={2025 17th International Conference on Knowledge and Smart Technology (KST)},
  pages={301--306},
  year={2025},
  organization={IEEE}
}

🌌 MARS: Foundational Mask Attention Refinement Model

Introduces a sequential quadtree attention strategy to refine segmentation masks, enhancing instance-level car damage detection accuracy. [Read on Springer]

@inproceedings{panboonyuen2023mars,
  title={Mars: Mask attention refinement with sequential quadtree nodes for car damage instance segmentation},
  author={Panboonyuen, Teerapong},
  booktitle={International Conference on Image Analysis and Processing},
  pages={28--38},
  year={2023},
  organization={Springer}
}

⚡ Quick Start

git clone https://github.com/kaopanboonyuen/MARS.git
cd MARS
python3 -m venv mars-env
source mars-env/bin/activate
pip install -r requirements.txt

GitHub Repository

📂 Datasets

Public Dataset
Private Dataset: Restricted (THAIVIVAT Insurance PCL)

✍️ Citation

@inproceedings{panboonyuen2023mars,
  title={MARS: Mask Attention Refinement with Sequential Quadtree Nodes},
  author={Panboonyuen, Teerapong},
  booktitle={ICIAP},
  year={2023},
  publisher={Springer}
}

🧠 Want to Know More About MARSAIL?

Explore how our lab is shaping the future of automotive AI, blending deep vision models with smart insurance tech. Get the full story, insights, and breakthroughs from the MARSAIL team in our feature blog post.

Read the Full Blog

🤝 Our Trusted Sponsors & Partners

We are deeply grateful for the invaluable support of our sponsors, partners, and collaborators. Their investment and belief in our mission empower MARSAIL to push boundaries in automotive AI.