VisionHOPE
Official PyTorch implementation of VisionHOPE: Visual Backbones as Self-Modifying Learning Systems.
VisionHOPE launched on 27 September 2026. It ranked #98 on Daily Launch on 25 October 2026 with a Launch Score of 19, from +59 stars on 25 Oct on GitHub. It moved down 28 places from the day before.
What is VisionHOPE?
PyTorch implementation of VisionHOPE, a visual backbone based on self-referential nested learning (SRNL). This repository provides ImageNet classification, COCO detection and instance segmentation, and ADE20K semantic segmentation, along with standalone SRNL and VisionHOPE operator modules. The hierarchical Tiny / Small / Base backbones support classification and dense prediction. For use in other architectures, see the standalone SRNL, operator, and block interfaces.
From its README on GitHub
VisionHOPE is a repo by PSRben on GitHub. It is written in Python and released under the MIT license.
How to get VisionHOPE
Get it from its repository on GitHub.