English

First Place Solution to the ECCV 2024 BRAVO Challenge: Evaluating Robustness of Vision Foundation Models for Semantic Segmentation

Computer Vision and Pattern Recognition 2024-10-10 v2 Artificial Intelligence Machine Learning Robotics

Abstract

In this report, we present the first place solution to the ECCV 2024 BRAVO Challenge, where a model is trained on Cityscapes and its robustness is evaluated on several out-of-distribution datasets. Our solution leverages the powerful representations learned by vision foundation models, by attaching a simple segmentation decoder to DINOv2 and fine-tuning the entire model. This approach outperforms more complex existing approaches, and achieves first place in the challenge. Our code is publicly available at https://github.com/tue-mps/benchmark-vfm-ss.

Keywords

Cite

@article{arxiv.2409.17208,
  title  = {First Place Solution to the ECCV 2024 BRAVO Challenge: Evaluating Robustness of Vision Foundation Models for Semantic Segmentation},
  author = {Tommie Kerssies and Daan de Geus and Gijs Dubbelman},
  journal= {arXiv preprint arXiv:2409.17208},
  year   = {2024}
}

Comments

v2 fixes ECE and FPR@95, among other small changes. arXiv admin note: substantial text overlap with arXiv:2409.15107