1 citations · 3 across the 9 of their papers we have counts for
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Cross-domain Few-shot Object Detection with Multi-modal Textual Enrichment
Zeyu Shangguan, Daniel Seita, Mohammad Rostami
Advancements in cross-modal feature extraction and integration have significantly enhanced performance in few-shot learning tasks. However, current multi-modal object detection (MM…
Cross-domain Multi-modal Few-shot Object Detection via Rich Text
Zeyu Shangguan, Daniel Seita, Mohammad Rostami
Cross-modal feature extraction and integration have led to steady performance improvements in few-shot learning tasks due to generating richer features. However, existing multi-mod…
Improved Region Proposal Network for Enhanced Few-Shot Object Detection
Zeyu Shangguan, Mohammad Rostami
Despite significant success of deep learning in object detection tasks, the standard training of deep neural networks requires access to a substantial quantity of annotated images…
Identification of Novel Classes for Improving Few-Shot Object Detection
Zeyu Shangguan, Mohammad Rostami
Conventional training of deep neural networks requires a large number of the annotated image which is a laborious and time-consuming task, particularly for rare objects. Few-shot o…