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Geunyoung Jung

2 accepted papers

2026

P3T: Prototypical Point-Level Prompt Tuning with Enhanced Generalization for 3D Vision-Language Models

ICRA 2026poster

With the rise of pre-trained models in the 3D point cloud domain for a wide range of real-world applications, adapting them to downstream tasks has become increasingly important. However, conventional full fine-tuning methods are computationally expensive and storage-intensive. Although prompt tunin…

2023

BlackVIP: Black-Box Visual Prompting for Robust Transfer Learning

CVPR 2023poster

With the surge of large-scale pre-trained models (PTMs), fine-tuning these models to numerous downstream tasks becomes a crucial problem. Consequently, parameter efficient transfer learning (PETL) of large models has grasped huge attention. While recent PETL methods showcase impressive performance,…