3 papers
cs.CV2026
TIPS Over Tricks: Simple Prompts for Effective Zero-shot Anomaly Detection
Alireza Salehi, Ehsan Karami, Sepehr Noey +4
Anomaly detection identifies departures from expected behavior in safety-critical settings. When target-domain normal data are unavailable, zero-shot anomaly detection (ZSAD) lever…
cs.CV2025
Crane: Context-Guided Prompt Learning and Attention Refinement for Zero-Shot Anomaly Detection
Alireza Salehi, Mohammadreza Salehi, Reshad Hosseini +3
Zero-shot anomaly detection and localization aims to learn from source-domain data and generalize to unseen target domains without target-domain samples. Recent CLIP-based methods…
cs.CV2025
Enhancing Interpretability of Sparse Latent Representations with Class Information
Farshad Sangari Abiz, Reshad Hosseini, Babak N. Araabi
Variational Autoencoders (VAEs) are powerful generative models for learning latent representations. Standard VAEs generate dispersed and unstructured latent spaces by utilizing all…