activity
20242026
collaborators
Showing 2024 · cs.CVShow all

5 papers · 2 filters

cs.CV2024

Redefining Normal: A Novel Object-Level Approach for Multi-Object Novelty Detection

Mohammadreza Salehi, Nikolaos Apostolikas, Efstratios Gavves +2

In the realm of novelty detection, accurately identifying outliers in data without specific class information poses a significant challenge. While current methods excel in single-o…

cs.CV2024

SelEx: Self-Expertise in Fine-Grained Generalized Category Discovery

Sarah Rastegar, Mohammadreza Salehi, Yuki M. Asano +2

In this paper, we address Generalized Category Discovery, aiming to simultaneously uncover novel categories and accurately classify known ones. Traditional methods, which lean heav…

cs.CV2024

Near, far: Patch-ordering enhances vision foundation models' scene understanding

Valentinos Pariza, Mohammadreza Salehi, Gertjan Burghouts +2

We introduce NeCo: Patch Neighbor Consistency, a novel self-supervised training loss that enforces patch-level nearest neighbor consistency across a student and teacher model. Comp…

cs.CV2024

SIGMA: Sinkhorn-Guided Masked Video Modeling

Mohammadreza Salehi, Michael Dorkenwald, Fida Mohammad Thoker +3

Video-based pretraining offers immense potential for learning strong visual representations on an unprecedented scale. Recently, masked video modeling methods have shown promising…

cs.CV2024

GeneralAD: Anomaly Detection Across Domains by Attending to Distorted Features

Luc P. J. Sträter, Mohammadreza Salehi, Efstratios Gavves +2

In the domain of anomaly detection, methods often excel in either high-level semantic or low-level industrial benchmarks, rarely achieving cross-domain proficiency. Semantic anomal…