no code implementations • 22 Mar 2024 • Jaeill Kim, Wonseok Lee, Moonjung Eo, Wonjong Rhee
Consequently, RFR achieves dual objectives in backward and forward compatibility: minimizing feature extractor modifications and enhancing novel task performance, respectively.
no code implementations • 11 Jan 2024 • Jaeill Kim, Duhun Hwang, Eunjung Lee, Jangwon Suh, Jimyeong Kim, Wonjong Rhee
In the past few years, contrastive learning has played a central role for the success of visual unsupervised representation learning.
no code implementations • 30 Aug 2023 • Kyungeun Lee, Jaeill Kim, Suhyun Kang, Wonjong Rhee
Contrastive learning has emerged as a cornerstone in recent achievements of unsupervised representation learning.
1 code implementation • CVPR 2023 • Jaeill Kim, Suhyun Kang, Duhun Hwang, Jungwook Shin, Wonjong Rhee
Since the introduction of deep learning, a wide scope of representation properties, such as decorrelation, whitening, disentanglement, rank, isotropy, and mutual information, have been studied to improve the quality of representation.
Ranked #15 on Domain Generalization on TerraIncognita
1 code implementation • 20 Mar 2023 • Jungwook Shin, Jaeill Kim, Kyungeun Lee, Hyunghun Cho, Wonjong Rhee
To improve the diversity of the whole-body object construction, we develop an iterative method that stochastically combines multiple objects observed from the real world into a single object.
no code implementations • 29 Sep 2021 • Jaeill Kim, Wonjong Rhee
In this work, we derive a principled non-contrastive method where mutual information is estimated as a difference of entropies and thus no need for negative sampling.