SiLAN augments target-neighborhood centroids with Gaussian noise whose variance comes from the frozen source model's neighbor dispersion, improving contrastive SFDA accuracy on three benchmarks.
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What Has Been Overlooked in Contrastive Source-Free Domain Adaptation: Leveraging Source-Informed Latent Augmentation within Neighborhood Context
SiLAN augments target-neighborhood centroids with Gaussian noise whose variance comes from the frozen source model's neighbor dispersion, improving contrastive SFDA accuracy on three benchmarks.