3 citations · 3 across the 1 of their papers we have counts for
3 papers
cs.CV2023
Collaborative Score Distillation for Consistent Visual Synthesis
Subin Kim, Kyungmin Lee, June Suk Choi +3
Generative priors of large-scale text-to-image diffusion models enable a wide range of new generation and editing applications on diverse visual modalities. However, when adapting…
cs.CV2023
S-CLIP: Semi-supervised Vision-Language Learning using Few Specialist Captions
Sangwoo Mo, Minkyu Kim, Kyungmin Lee +1
Vision-language models, such as contrastive language-image pre-training (CLIP), have demonstrated impressive results in natural image domains. However, these models often struggle…
cs.LG2023★ 3 cited
STUNT: Few-shot Tabular Learning with Self-generated Tasks from Unlabeled Tables
Jaehyun Nam, Jihoon Tack, Kyungmin Lee +2
Learning with few labeled tabular samples is often an essential requirement for industrial machine learning applications as varieties of tabular data suffer from high annotation co…