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COSTARR: Consolidated Open Set Technique with Attenuation for Robust Recognition

📄 Paper: COSTARR (ICCV 2025)

COSTARR uses feature attenuation to generate a COSTARR score which normalizes the scaled prediction logit for Open-Set Recognition.

Setup

  1. Prepare extracted logit and feature vector numpy (.npy) files according to the structure and naming in COSTARR_Driver for each Known/Unknown Dataset you will test. Update the Extractions folder in COSTARR_Driver.py to auto-detect these files.
  2. Modify the weights in COSTARR_Driver.py to load weights from your target architecture.
  3. Running COSTARR_Driver.py will produce a system/architecture-named folder in COSTARR_Experiments/ containing output numpy files (.npy) in the following format per row: [gt, predition, score].

Note

COSTARR.py contains the class-level implementation of COSTARR which can be integrated into other projects.

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