16 citations · 40 across the 9 of their papers we have counts for
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cs.CV2024
OurDB: Ouroboric Domain Bridging for Multi-Target Domain Adaptive Semantic Segmentation
Seungbeom Woo, Geonwoo Baek, Taehoon Kim +3
Multi-target domain adaptation (MTDA) for semantic segmentation poses a significant challenge, as it involves multiple target domains with varying distributions. The goal of MTDA i…
cs.CV2024★ 1 cited
Semantic Prompting with Image-Token for Continual Learning
Jisu Han, Jaemin Na, Wonjun Hwang
Continual learning aims to refine model parameters for new tasks while retaining knowledge from previous tasks. Recently, prompt-based learning has emerged to leverage pre-trained…
cs.CV2024★ 1 cited
D3T: Distinctive Dual-Domain Teacher Zigzagging Across RGB-Thermal Gap for Domain-Adaptive Object Detection
Dinh Phat Do, Taehoon Kim, Jaemin Na +4
Domain adaptation for object detection typically entails transferring knowledge from one visible domain to another visible domain. However, there are limited studies on adapting fr…