AI BriefingVisionHOPE: VisionHOPE: A Vision Backbone That Self-Modifies Its Structure
PSRben/VisionHOPE
About the project
A vision backbone that applies the 'Self-Modifying' concept, allowing it to modify its own structure during the learning process, breaking free from fixed architectures. It aims for a dynamic learning system that goes beyond the limitations of existing CNNs and Transformers.
It supports various computer vision tasks, including ImageNet-1K classification, COCO object detection and instance segmentation, and ADE20K semantic segmentation. It provides pretrained weights in three sizes—Tiny, Small, and Base—allowing users to select the appropriate model for their hardware environment.
Designed as an alternative to standard backbones such as Mask R-CNN and UPerNet. Implemented in PyTorch and released under the MIT license, it can be freely used within the open-source ecosystem.
PSRben/VisionHOPE
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image-classification
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