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20192024
most citedLearning Cross-Scale Weighted Prediction for Efficient Neural Video Compression

31 citations · 51 across the 11 of their papers we have counts for

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9 papers · 1 filter

eess.IV2024

UniMIC: Towards Universal Multi-modality Perceptual Image Compression

Yixin Gao, Xin Li, Xiaohan Pan +5

We present UniMIC, a universal multi-modality image compression framework, intending to unify the rate-distortion-perception (RDP) optimization for multiple image codecs simultaneo…

eess.IV2024

Conditional Neural Video Coding with Spatial-Temporal Super-Resolution

Henan Wang, Xiaohan Pan, Runsen Feng +2

This document is an expanded version of a one-page abstract originally presented at the 2024 Data Compression Conference. It describes our proposed method for the video track of th…

eess.IV2023

Exploring the Rate-Distortion-Complexity Optimization in Neural Image Compression

Yixin Gao, Runsen Feng, Zongyu Guo +1

Despite a short history, neural image codecs have been shown to surpass classical image codecs in terms of rate-distortion performance. However, most of them suffer from significan…

eess.IV2021★ 31 cited

Learning Cross-Scale Weighted Prediction for Efficient Neural Video Compression

Zongyu Guo, Runsen Feng, Zhizheng Zhang +2

Neural video codecs have demonstrated great potential in video transmission and storage applications. Existing neural hybrid video coding approaches rely on optical flow or Gaussia…

eess.IV2021★ 5 cited

Versatile Learned Video Compression

Runsen Feng, Zongyu Guo, Zhizheng Zhang +1

Learned video compression methods have demonstrated great promise in catching up with traditional video codecs in their rate-distortion (R-D) performance. However, existing learned…

eess.IV2021

Soft then Hard: Rethinking the Quantization in Neural Image Compression

Zongyu Guo, Zhizheng Zhang, Runsen Feng +1

Quantization is one of the core components in lossy image compression. For neural image compression, end-to-end optimization requires differentiable approximations of quantization,…