VisionHOPE — visual backbones as self-modifying learning systems
Official pretrained weights for 'VisionHOPE: Visual Backbones as Self-Modifying Learning Systems' — hierarchical VisionHOPE-T/S/B checkpoints for ImageNet-1K classification, COCO detection/instance segmentation, ADE20K semantic segmentation.
Why it matters
Research architecture framing visual backbones as self-modifying learning systems, released with T/S/B sizes across classification, detection, and segmentation.
What you could build with it
A vision research team can benchmark VisionHOPE backbones against ViT/Swin baselines on their own detection/segmentation tasks.
Does it hold up?
Too early to judge — 137 downloads, weights-only release.
Learn more
First spotted on hf: source.
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