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cs.CV2024
Improving Image Clustering with Artifacts Attenuation via Inference-Time Attention Engineering
Kazumoto Nakamura, Yuji Nozawa, Yu-Chieh Lin +2
The goal of this paper is to improve the performance of pretrained Vision Transformer (ViT) models, particularly DINOv2, in image clustering task without requiring re-training or f…
cs.CV2024
Revisiting Relevance Feedback for CLIP-based Interactive Image Retrieval
Ryoya Nara, Yu-Chieh Lin, Yuji Nozawa +4
Many image retrieval studies use metric learning to train an image encoder. However, metric learning cannot handle differences in users' preferences, and requires data to train an…