VidEoMT: Your ViT is Secretly Also a Video Segmentation Model
Existing online video segmentation models typically combine a per-frame segmenter with complex specialized tracking modules. While effective, these modules introduce significant architectural complexity and computational overhead. Recent studies suggest that plain Vision Transformer (ViT) encoders, when scaled with sufficient capacity and large-scale pre-training, can conduct accurate image segmentation without requiring specialized modules. Motivated by this observation, we propose the Video Encoder-only Mask Transformer (VidEoMT), a simple encoder-only video segmentation model that eliminates the need for dedicated tracking modules. To enable temporal modeling in an encoder-only ViT, Vi...
| Authors | Narges Norouzi, Idil Esen Zulfikar, Niccolò Cavagnero et al. |
|---|---|
| Primary category | cs.CV |
| Published | 19 February 2026 |
| Last updated at source | 4 March 2026 |
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