19 citations · 20 across the 4 of their papers we have counts for
4 papers
PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation
Uyoung Jeong, Jonathan Freer, Seungryul Baek +2
We study multi-dataset training (MDT) for pose estimation, where skeletal heterogeneity presents a unique challenge that existing methods have yet to address. In traditional domain…
REP: Resource-Efficient Prompting for Rehearsal-Free Continual Learning
Sungho Jeon, Xinyue Ma, Kwang In Kim +1
Recent rehearsal-free continual learning (CL) methods guided by prompts achieve strong performance on vision tasks with non-stationary data but remain resource-intensive, hindering…
In Search of a Data Transformation That Accelerates Neural Field Training
Junwon Seo, Sangyoon Lee, Kwang In Kim +1
Neural field is an emerging paradigm in data representation that trains a neural network to approximate the given signal. A key obstacle that prevents its widespread adoption is th…
Task-Aware Variational Adversarial Active Learning
Kwanyoung Kim, Dongwon Park, Kwang In Kim +1
Often, labeling large amount of data is challenging due to high labeling cost limiting the application domain of deep learning techniques. Active learning (AL) tackles this by quer…