mlsanityData to 7 Oct 2026

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

arXiv 2409.17208 ↗First posted 25 Sep 2024cs.CV cs.AI cs.LGcited by 3

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Abstract (arXiv)

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.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 17 of its 20 references that are in the map. First posted on arXiv 25 Sep 2024.

Builds on

17 of 20 references.

References · 17

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  3. 2023DINOv2: Learning Robust Visual Features without Supervisioncited by 7,764
  4. 2016The Cityscapes Dataset for Semantic Urban Scene Understandingcited by 4,427
  5. 2023Sigmoid Loss for Language Image Pre-Trainingcited by 3,048
  6. 2021BEiT: BERT Pre-Training of Image Transformerscited by 2,360
  7. 2021Masked-attention Mask Transformer for Universal Image Segmentationcited by 2,338
  8. 2022Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language Taskscited by 510
  9. 2022DeiT III: Revenge of the ViTcited by 417
  10. 2023EVA-02: A Visual Representation for Neon Genesiscited by 377
  11. 2021SegmentMeIfYouCan: A Benchmark for Anomaly Segmentationcited by 150
  12. 2020How to Train Neural Networks for Flare Removalcited by 50
5 more
  1. 2023Reliability in Semantic Segmentation: Can We Use Synthetic Data?cited by 24
  2. 2024How to Benchmark Vision Foundation Models for Semantic Segmentation?cited by 15
  3. 2024Exploring the Benefits of Vision Foundation Models for Unsupervised Domain Adaptationcited by 11
  4. 2021Physics-informed Guided Disentanglement in Generative Networkscited by 9
  5. 2024The BRAVO Semantic Segmentation Challenge Results in UNCV2024cited by 6

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Cited by year

Citing papers per year: 2025: 3.

3 papers.

  1. 2025Your ViT is Secretly an Image Segmentation Modelcited by 61
  2. 2025Simplifying Traffic Anomaly Detection with Video Foundation Modelscited by 3
  3. 2025What is the Added Value of UDA in the VFM Era?cited by 1