1 citations · 1 across the 2 of their papers we have counts for
3 papers
SNAP: Low-Latency Test-Time Adaptation with Sparse Updates
Hyeongheon Cha, Dong Min Kim, Hye Won Chung +2
Test-Time Adaptation (TTA) adjusts models using unlabeled test data to handle dynamic distribution shifts. However, existing methods rely on frequent adaptation and high computatio…
QuRe: Query-Relevant Retrieval through Hard Negative Sampling in Composed Image Retrieval
Jaehyun Kwak, Ramahdani Muhammad Izaaz Inhar, Se-Young Yun +1
Composed Image Retrieval (CIR) retrieves relevant images based on a reference image and accompanying text describing desired modifications. However, existing CIR methods only focus…
Test-Time Adaptation with Binary Feedback
Taeckyung Lee, Sorn Chottananurak, Junsu Kim +3
Deep learning models perform poorly when domain shifts exist between training and test data. Test-time adaptation (TTA) is a paradigm to mitigate this issue by adapting pre-trained…