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]]> https://mcl.korea.ac.kr/jsjang-2026neurips/feed/ 0 [NeurIPS2026] Learned progressive image compression https://mcl.korea.ac.kr/neurips2026-learned-progressive-image-compression/ https://mcl.korea.ac.kr/neurips2026-learned-progressive-image-compression/#comments Mon, 28 Sep 2026 01:10:35 +0000 Chang-Su Kim http://mcl.korea.ac.kr/?p=45750
ACCEPTED TO NeurIPS 2026

Bound-Conditioned Latent Inference for Progressive Image Compression

We are glad to announce that our paper, BLI, has been accepted to NeurIPS 2026!

BLI continues our lab’s research on progressive image compression, following DPICT (CVPR 2022) and CTC (CVPR 2023). This series explores how a single compressed bitstream can support a wide range of bitrates, progressively improving image quality as more bits are received.

Starting with trit-plane coding in DPICT and advancing to context-based coding in CTC, we now take another step forward with BLI.

  1. Jaeseok Jang*, Seungmin Jeon*, Kwang Pyo Choi, and Chang-Su Kim, “Bound-Conditioned Latent Inference for Progressive Image Compression,” NeurIPS 2026. (BLI)
  2. Seungmin Jeon, Kwang Pyo Choi, Youngo Park, and Chang-Su Kim, “Context-Based Trit-Plane Coding for Progressive Image Compression,” CVPR 2023. (CTC)
  3. Jae-Han Lee, Seungmin Jeon, Kwang Pyo Choi, Youngo Park, and Chang-Su Kim, “DPICT: Deep Progressive Image Compression Using Trit-Planes,” CVPR 2022. (DPICT)

* Equal contribution.

Congratulations to Jaeseok and Seungmin! Our images improve progressively, and so does our research.

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