3 citations · 6 across the 4 of their papers we have counts for
4 papers
Contrastive Order Learning: A General Framework for Ordinal Regression
Chaewon Lee, BeomJun Shim, Kwang Pyo Choi +1
We propose contrastive order learning (ConOrd), a contrastive learning framework for ordinal regression that integrates the strengths of contrastive learning and order learning. Wh…
Context-Based Trit-Plane Coding for Progressive Image Compression
Seungmin Jeon, Kwang Pyo Choi, Youngo Park +1
Trit-plane coding enables deep progressive image compression, but it cannot use autoregressive context models. In this paper, we propose the context-based trit-plane coding (CTC) a…
Learning Local Implicit Fourier Representation for Image Warping
Jaewon Lee, Kwang Pyo Choi, Kyong Hwan Jin
Image warping aims to reshape images defined on rectangular grids into arbitrary shapes. Recently, implicit neural functions have shown remarkable performances in representing imag…
DPICT: Deep Progressive Image Compression Using Trit-Planes
Jae-Han Lee, Seungmin Jeon, Kwang Pyo Choi +2
We propose the deep progressive image compression using trit-planes (DPICT) algorithm, which is the first learning-based codec supporting fine granular scalability (FGS). First, we…