[WACV2025] SUM: Saliency Unification through Mamba for Visual Attention Modeling
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Updated
Dec 8, 2024 - Python
[WACV2025] SUM: Saliency Unification through Mamba for Visual Attention Modeling
The code for the paper "Efficient Self-Supervised Video Hashing with Selective State Spaces" (AAAI'25).
Satellite-Image-Alignment-Differencing-and-Segmentation
Segmentation of cancerous tumors using Mamba. Code, resources, and paper provided. We manage to make a small (42k param) model that can segment pretty well.
This Mamba-based model is used to classify skin cancer. After 20 epochs training, this model can achieve 99% accuracy in binary-classification task.
Fork of MAMBA mathematical morphology library http://www.mamba-image.org
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