1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CV2026
Seeing Before Synthesizing: VLM-Guided Transition Event Discovery for Weakly-Supervised Dense Video Captioning
Ye-Chan Kim, Seunghee Choi, SeungJu Cha +4
Weakly-Supervised Dense Video Captioning aims to localize and describe multiple events in untrimmed videos given only an ordered set of event-level captions per video. Recent work…
cs.CV2026
SAIL: Similarity-Aware Guidance and Inter-Caption Augmentation-based Learning for Weakly-Supervised Dense Video Captioning
Ye-Chan Kim, SeungJu Cha, Si-Woo Kim +3
Weakly-Supervised Dense Video Captioning aims to localize and describe events in videos trained only on caption annotations, without temporal boundaries. Prior work introduced an i…
eess.IV2025★ 1 cited
Pathological MRI Segmentation by Synthetic Pathological Data Generation in Fetuses and Neonates
Misha P. T Kaandorp, Damola Agbelese, Hosna Asma-ull +6
Developing new methods for the automated analysis of clinical fetal and neonatal MRI data is limited by the scarcity of annotated pathological datasets and privacy concerns that of…