Context-Based Trit-Plane Coding for Progressive Image Compression

1 code implementation • CVPR 2023 • Seungmin Jeon, Kwang Pyo Choi, Youngo Park, Chang-Su Kim

Trit-plane coding enables deep progressive image compression, but it cannot use autoregressive context models.

Image Compression

Scalable Object Detection on Embedded Devices Using Weight Pruning and Singular Value Decomposition

no code implementations • 5 Mar 2023 • Dohyun Ham, Jaeyeop Jeong, June-Kyoo Park, Raehyeon Jeong, Seungmin Jeon, Hyeongjun Jeon, Yewon Lim

The proposed method was evaluated on a custom dataset of street work images obtained from https://universe. roboflow. com/roboflow-100/street-work.

object-detection Object Detection

RD-Optimized Trit-Plane Coding of Deep Compressed Image Latent Tensors

no code implementations • 25 Mar 2022 • Seungmin Jeon, Jae-Han Lee, Chang-Su Kim

DPICT is the first learning-based image codec supporting fine granular scalability.

DPICT: Deep Progressive Image Compression Using Trit-Planes

1 code implementation • CVPR 2022 • Jae-Han Lee, Seungmin Jeon, Kwang Pyo Choi, Youngo Park, Chang-Su Kim

We propose the deep progressive image compression using trit-planes (DPICT) algorithm, which is the first learning-based codec supporting fine granular scalability (FGS).

Image Compression