6 citations · 14 across the 8 of their papers we have counts for
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cs.LG2023★ 1 cited
Layer-wise Auto-Weighting for Non-Stationary Test-Time Adaptation
Junyoung Park, Jin Kim, Hyeongjun Kwon +2
Given the inevitability of domain shifts during inference in real-world applications, test-time adaptation (TTA) is essential for model adaptation after deployment. However, the re…
cs.CV2023★ 3 cited
Knowing Where to Focus: Event-aware Transformer for Video Grounding
Jinhyun Jang, Jungin Park, Jin Kim +2
Recent DETR-based video grounding models have made the model directly predict moment timestamps without any hand-crafted components, such as a pre-defined proposal or non-maximum s…
cs.CV2023
Probabilistic Prompt Learning for Dense Prediction
Hyeongjun Kwon, Taeyong Song, Somi Jeong +3
Recent progress in deterministic prompt learning has become a promising alternative to various downstream vision tasks, enabling models to learn powerful visual representations wit…