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Model Weight Released

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@@ -10,6 +10,9 @@ International Conference on Learning Representations (ICLR) 2023\
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  ## Updates
 
 
 
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  ***2/10/2023***\
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  RevCol model weights released.
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@@ -26,16 +29,12 @@ Initial commits: codes for ImageNet-1k and ImageNet-22k classification are relea
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  - [x] ImageNet-1K and 22k Training Code
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  - [x] ImageNet-1K and 22k Model Weights
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  - [x] Cascade Mask R-CNN COCO Object Detection Code & Model Weights
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- - [ ] ADE20k Semantic Segmentation Code & Model Weights
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  ## Introduction
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  RevCol is composed of multiple copies of subnetworks, named columns respectively, between which multi-level reversible connections are employed. RevCol coud serves as a foundation model backbone for various tasks in computer vision including classification, detection and segmentation.
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- <p align="center">
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- <img src="https://huggingface.co/LarryTsai/RevCol/blob/main/figures/title.png" width=100% height=100%
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- class="center">
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- </p>
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  ## Main Results on ImageNet with Pre-trained Models
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  ## Updates
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+ ***3/9/2023***\
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+ RevCol Detection & Segmentation model weights released.
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+
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  ***2/10/2023***\
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  RevCol model weights released.
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  - [x] ImageNet-1K and 22k Training Code
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  - [x] ImageNet-1K and 22k Model Weights
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  - [x] Cascade Mask R-CNN COCO Object Detection Code & Model Weights
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+ - [x] ADE20k Semantic Segmentation Code & Model Weights
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  ## Introduction
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  RevCol is composed of multiple copies of subnetworks, named columns respectively, between which multi-level reversible connections are employed. RevCol coud serves as a foundation model backbone for various tasks in computer vision including classification, detection and segmentation.
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  ## Main Results on ImageNet with Pre-trained Models
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