3 papers
cs.CV2026
Fourier Self-Supervision for Fine-Grained Generalized Category Discovery
Sarah Rastegar, Mina Ghadimi Atigh, Pascal Mettes +2
Generalized Category Discovery aims to recognize known categories while identifying novel ones within unlabeled data. Existing methods, typically based on self-supervision and cont…
cs.CV2025
InfSplign: Inference-Time Spatial Alignment of Text-to-Image Diffusion Models
Sarah Rastegar, Violeta Chatalbasheva, Sieger Falkena +5
Text-to-image (T2I) diffusion models generate high-quality images but often fail to capture the spatial relations specified in text prompts. This limitation can be traced to two fa…
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…