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- ---
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- license: mit
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- ---
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-
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- # HIPIE: Hierarchical Open-vocabulary Universal Image Segmentation
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-
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- PyTorch implementation of HIPIE from ["Hierarchical Open-vocabulary Universal Image Segmentation"](https://arxiv.org/abs/2307.00764) (Wang et al., NeurIPS 2023).
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-
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- ## Pretrained Weights
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-
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- We provide ViT-H and ResNet-50 weights for hierarchical and part-aware image segmentation across multiple datasets:
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-
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- | Format | Filename | Description |
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- |--------|----------|-------------|
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- | ViT-H (O365, COCO, RefCOCO, PACO) | `vit_h_cloud.pth` | Pretrained with O365,COCO,RefCOCO,PACO |
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- | ViT-H (COCO, RefCOCO, Pascal-Parts) | `vit_h_cloud_parts.pth` | Finetuned on COCO,RefCOCO,Pascal-Parts |
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- | ResNet-50 (Pascal-Parts) | `r50_parts.pth` | Pretrained with O365,COCO,RefCOCO,Pascal Panoptic Parts |
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-
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- ## Usage
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-
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- For demo notebooks, model configs, and inference scripts, see the [GitHub repository](https://github.com/berkeley-hipie/HIPIE).
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-
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- ## Citation
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-
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- @inproceedings{wang2023hierarchical,
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- title={Hierarchical Open-vocabulary Universal Image Segmentation},
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- author={Wang, Xudong and Li, Shufan and Kallidromitis, Konstantinos and Kato, Yusuke and Kozuka, Kazuki and Darrell, Trevor},
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- booktitle={Thirty-seventh Conference on Neural Information Processing Systems},
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- year={2023}
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- }
 
 
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+ ---
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+ license: mit
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+ ---
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+
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+ # HIPIE: Hierarchical Open-vocabulary Universal Image Segmentation
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+
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+ PyTorch implementation of HIPIE from ["Hierarchical Open-vocabulary Universal Image Segmentation"](https://arxiv.org/abs/2307.00764) (Wang et al., NeurIPS 2023).
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+
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+ ## Pretrained Weights
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+
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+ We provide ViT-H and ResNet-50 weights for hierarchical and part-aware image segmentation across multiple datasets:
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+
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+ | Format | Filename | Description |
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+ |--------|----------|-------------|
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+ | ViT-H (O365, COCO, RefCOCO, PACO) | `vit_h_cloud.pth` | Pretrained with O365,COCO,RefCOCO,PACO |
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+ | ViT-H (COCO, RefCOCO, Pascal-Parts) | `vit_h_cloud_parts.pth` | Finetuned on COCO,RefCOCO,Pascal-Parts |
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+ | ResNet-50 (Pascal-Parts) | `r50_parts.pth` | Pretrained with O365,COCO,RefCOCO,Pascal Panoptic Parts |
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+
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+ ## Usage
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+
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+ For demo notebooks, model configs, and inference scripts, see the [GitHub repository](https://github.com/berkeley-hipie/HIPIE).
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+
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+ ## Citation
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+ ```
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+ @inproceedings{wang2023hierarchical,
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+ title={Hierarchical Open-vocabulary Universal Image Segmentation},
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+ author={Wang, Xudong and Li, Shufan and Kallidromitis, Konstantinos and Kato, Yusuke and Kozuka, Kazuki and Darrell, Trevor},
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+ booktitle={Thirty-seventh Conference on Neural Information Processing Systems},
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+ year={2023}
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+ }
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+ ```