EoMT

EoMT (Encoder-only Mask Transformer) is a Vision Transformer (ViT) architecture designed for high-quality and efficient image segmentation. It was introduced in the CVPR 2025 highlight paper:
Your ViT is Secretly an Image Segmentation Model
by Tommie Kerssies, Niccolò Cavagnero, Alexander Hermans, Narges Norouzi, Giuseppe Averta, Bastian Leibe, Gijs Dubbelman, and Daan de Geus.

Key Insight: Given sufficient scale and pretraining, a plain ViT along with additional few params can perform segmentation without the need for task-specific decoders or pixel fusion modules. The same model backbone supports semantic, instance, and panoptic segmentation with different post-processing 🤗

The original implementation can be found in this repository.

The HuggingFace model page is available at this link.

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How to use

Here is how to use this model for Panotpic Segmentation:

import matplotlib.pyplot as plt
import requests
import torch
from PIL import Image

from transformers import EomtForUniversalSegmentation, AutoImageProcessor


model_id = "tue-mps/coco_panoptic_eomt_base_640_2x"
processor = AutoImageProcessor.from_pretrained(model_id)
model = EomtForUniversalSegmentation.from_pretrained(model_id)

image = Image.open(requests.get("http://images.cocodataset.org/val2017/000000039769.jpg", stream=True).raw)

inputs = processor(
    images=image,
    return_tensors="pt",
)

with torch.inference_mode():
    outputs = model(**inputs)

# Prepare the original image size in the format (height, width)
target_sizes = [(image.height, image.width)]

# Post-process the model outputs to get final segmentation prediction
preds = processor.post_process_panoptic_segmentation(
    outputs,
    target_sizes=target_sizes,
)

# Visualize the panoptic segmentation mask
plt.imshow(preds[0]["segmentation"])
plt.axis("off")
plt.title("Panoptic Segmentation")
plt.show()

Citation

If you find our work useful, please consider citing us as:

@inproceedings{kerssies2025eomt,
  author    = {Kerssies, Tommie and Cavagnero, Niccolò and Hermans, Alexander and Norouzi, Narges and Averta, Giuseppe and Leibe, Bastian and Dubbelman, Gijs and de Geus, Daan},
  title     = {Your ViT is Secretly an Image Segmentation Model},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year      = {2025},
}