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Depth Head Kitti

Monocular depth estimation head trained on KITTI (RMSE: 2.79). Part of A Frame is Worth One Token: Efficient Generative World Modeling with Delta Tokens (CVPR 2026 Highlight).

Quellehuggingface.co/Amazon-FAR/depth-head-kitti/tree/87e1f23886fbe152cdddfc77bae21287e8dc6693

ArtOtherVersionPytorch modelCBewertung

Modellquelle

Art: Other
Dateigröße: 784 KB
Version: vPytorch model
Aktualisiert: 20. Okt. 2026
Quelle: Hugging Face

Quellenbeschreibung

Depth Head — KITTI

Monocular depth estimation head trained on KITTI (RMSE: 2.79). Part of A Frame is Worth One Token: Efficient Generative World Modeling with Delta Tokens (CVPR 2026 Highlight).

Usage

Requires a frozen DINOv3 ViT-B backbone. See the DeltaTok GitHub repository for training and evaluation code.

Acknowledgements

DINOv3
KITTI

Citation

@inproceedings{kerssies2026deltatok,
  title     = {A Frame is Worth One Token: Efficient Generative World Modeling with Delta Tokens},
  author    = {Kerssies, Tommie and Berton, Gabriele and He, Ju and Yu, Qihang and Ma, Wufei and de Geus, Daan and Dubbelman, Gijs and Chen, Liang-Chieh},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year      = {2026}
}

Quellen

1 Quelle

Hugging FacePrimärVersion 87e1f23886fbe152cdddfc77bae21287e8dc6693

huggingface.co/Amazon-FAR/depth-head-kitti/tree/87e1f23886fbe152cdddfc77bae21287e8dc6693

Verifiziert 20. Okt.

Modellartefakte

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pytorch_model.bin

bin · 784 KB · SHA-256 a05336ed06c2…2b5b · Hugging Face

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Quellenauszüge

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Readme3. Aug.huggingface.co/Amazon-FAR/depth-head-kitti

--- datasets: - kitti library_name: pytorch license: apache-2.0 pipeline_tag: depth-estimation tags: - deltatok - cvpr2026-highlight --- # Depth Head — KITTI Monocular depth estimation head trained on KITTI (RMSE: 2.79). Part of [A Frame is Worth One Token: Efficient Generative World Modeling with Delta Tokens](https://huggingface.co/papers/2604.04913) (CVPR 2026 Highlight). ## Usage Requires a frozen [DINOv3](https://github.com/facebookresearch/dinov3) ViT-B backbone. See the [DeltaTok GitHub repository](https://github.com/amazon-far/deltatok) for training and evaluation code. ## Acknowledgements - [DINOv3](https://github.com/facebookresearch/dinov3) - [KITTI](https://www.cvlibs.net/datasets/kitti/) ## Citation ```bibtex @inproceedings{kerssies2026deltatok, title = {A Frame is Worth One Token: Efficient Generative World Modeling with Delta Tokens}, author = {Kerssies, Tommie and Berton, Gabriele and He, Ju and Yu, Qihang and Ma, Wufei and de Geus, Daan and Dubbelman, Gijs and Chen, Liang-Chieh}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2026} } ```

Note3. Aug.huggingface.co/Amazon-FAR/depth-head-kitti

Source context: 0 downloads · 1 likes · Pipeline depth-estimation · Library pytorch · Repo Amazon-FAR/depth-head-kitti