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cs.CV2026
PersonaDrive: Controllable Trajectory Prediction with Multi-Dimensional Driving Personas
Chan Lee, Kimin Yun, Yuseok Bae +2
Although recent trajectory prediction and end-to-end autonomous driving methods improve robustness in urban environments, they still lack meaningful controllability. Existing bench…
cs.CV2026
Learning to Orchestrate Vision Foundation Models for Multi-Task Dense Prediction
Donghyun Han, Yuseok Bae, Jung Uk Kim +1
Vision foundation models (VFMs) exhibit complementary strengths shaped by their pretraining objectives. Yet prevailing methods for multi-task dense prediction still train an entire…
cs.CV2024
Task-Specific Adaptation of Segmentation Foundation Model via Prompt Learning
Hyung-Il Kim, Kimin Yun, Jun-Seok Yun +1
Recently, foundation models trained on massive datasets to adapt to a wide range of tasks have attracted considerable attention and are actively being explored within the computer…