tue-mps/videomt-dinov2-small-ytvis2019

VidEoMT-S on YouTube-VIS 2019

This repository contains the Hugging Face Transformers conversion of the official VidEoMT checkpoint yt_2019_vit_small_52.8.pth from tue-mps/VidEoMT.

Model details

• Architecture: VidEoMT with a DINOv2 ViT-S/14 with 4 register tokens backbone
• Task: video instance segmentation
• Dataset: YouTube-VIS 2019
• Input resolution: 640 x 640
• Number of frames: 2
• Paper: Your ViT is Secretly Also a Video Segmentation Model

Reported metrics

Metric	Value
AP	52.8
AR@10	62.2
FPS	294

The metrics above are the numbers reported by the authors in the official model zoo.

Usage

from transformers import AutoModelForUniversalSegmentation, AutoVideoProcessor

model_id = "tue-mps/videomt-dinov2-small-ytvis2019"
processor = AutoVideoProcessor.from_pretrained(model_id)
model = AutoModelForUniversalSegmentation.from_pretrained(model_id)

Use processor.post_process_instance_segmentation, processor.post_process_panoptic_segmentation, or processor.post_process_semantic_segmentation depending on the target task.