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cs.CV2025
Leveraging Generative AI Models to Explore Human Identity
Yunha Yeo, Daeho Um
This paper attempts to explore human identity by utilizing neural networks in an indirect manner. For this exploration, we adopt diffusion models, state-of-the-art AI generative mo…
cs.CV2025
Enhancing Weakly Supervised Video Grounding via Diverse Inference Strategies for Boundary and Prediction Selection
Sunoh Kim, Daeho Um
Weakly supervised video grounding aims to localize temporal boundaries relevant to a given query without explicit ground-truth temporal boundaries. While existing methods primarily…