12 citations · 14 across the 10 of their papers we have counts for
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cs.CV2026
Preserve the Hard, Regenerate the Rest: Uncertainty-Guided Synthetic Training Data Augmentation with Diffusion Models
Nikolai Röhrich, Julian Gleißner, Ahmed H. A. Ibrahim +2
Semantic segmentation models struggle with data sparsity and rare or visually diverse regions, e.g., dense regions or small objects in aerial or autonomous mobility data. While syn…
cs.CV2026
Video Joint-Embedding Predictive Architectures for Facial Expression Recognition
Lennart Eing, Cristina Luna-Jiménez, Silvan Mertes +1
This paper introduces a novel application of Video Joint-Embedding Predictive Architectures (V-JEPAs) for Facial Expression Recognition (FER). Departing from conventional pre-train…