3 citations · 5 across the 4 of their papers we have counts for
5 papers
Bound-Conditioned Latent Inference for Progressive Image Compression
Jaeseok Jang, Seungmin Jeon, Kwang Pyo Choi +1
Progressive image compression reconstructs images from prefixes of a single bitstream and therefore involves sequential latent inference under partial observations. Existing trit-p…
Scalable Object Detection on Embedded Devices Using Weight Pruning and Singular Value Decomposition
Dohyun Ham, Jaeyeop Jeong, June-Kyoo Park +4
This paper presents a method for optimizing object detection models by combining weight pruning and singular value decomposition (SVD). The proposed method was evaluated on a custo…
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…
RD-Optimized Trit-Plane Coding of Deep Compressed Image Latent Tensors
Seungmin Jeon, Jae-Han Lee, Chang-Su Kim
DPICT is the first learning-based image codec supporting fine granular scalability. In this paper, we describe how to implement two key components of DPICT efficiently: trit-plane…
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…