activity
20212026
collaborators

5 papers

cs.CV2026

STEP: Score-Based Temporal Energy for Human Pose Video Anomaly Detection

Jakub Micorek, Mateusz Koziński, Horst Possegger

Skeleton-based Video Anomaly Detection (VAD) offers a robust, privacy-preserving solution for identifying abnormal behaviors. To model the distribution of normal static and moving…

cs.CV2024

MULDE: Multiscale Log-Density Estimation via Denoising Score Matching for Video Anomaly Detection

Jakub Micorek, Horst Possegger, Dominik Narnhofer +2

We propose a novel approach to video anomaly detection: we treat feature vectors extracted from videos as realizations of a random variable with a fixed distribution and model this…

cs.CV2024

Meta-Prompting for Automating Zero-shot Visual Recognition with LLMs

M. Jehanzeb Mirza, Leonid Karlinsky, Wei Lin +5

Prompt ensembling of Large Language Model (LLM) generated category-specific prompts has emerged as an effective method to enhance zero-shot recognition ability of Vision-Language M…

cs.CV2023

Sit Back and Relax: Learning to Drive Incrementally in All Weather Conditions

Stefan Leitner, M. Jehanzeb Mirza, Wei Lin +5

In autonomous driving scenarios, current object detection models show strong performance when tested in clear weather. However, their performance deteriorates significantly when te…

cs.CV2021

The Norm Must Go On: Dynamic Unsupervised Domain Adaptation by Normalization

M. Jehanzeb Mirza, Jakub Micorek, Horst Possegger +1

Domain adaptation is crucial to adapt a learned model to new scenarios, such as domain shifts or changing data distributions. Current approaches usually require a large amount of l…