7 citations · 10 across the 9 of their papers we have counts for
6 papers · 1 filter
MLICv2: Enhanced Multi-Reference Entropy Modeling for Learned Image Compression
Wei Jiang, Yongqi Zhai, Jiayu Yang +2
Recent advances in learned image compression (LIC) have achieved remarkable performance improvements over traditional codecs. Notably, the MLIC series-LICs equipped with multi-refe…
DeepFGS: Fine-Grained Scalable Coding for Learned Image Compression
Yongqi Zhai, Yi Ma, Luyang Tang +2
Scalable coding, which can adapt to channel bandwidth variation, performs well in today's complex network environment. However, most existing scalable compression methods face two…
ECVC: Exploiting Non-Local Correlations in Multiple Frames for Contextual Video Compression
Wei Jiang, Junru Li, Kai Zhang +1
In Learned Video Compression (LVC), improving inter prediction, such as enhancing temporal context mining and mitigating accumulated errors, is crucial for boosting rate-distortion…
LVC-LGMC: Joint Local and Global Motion Compensation for Learned Video Compression
Wei Jiang, Junru Li, Kai Zhang +1
Existing learned video compression models employ flow net or deformable convolutional networks (DCN) to estimate motion information. However, the limited receptive fields of flow n…
MLIC++: Linear Complexity Multi-Reference Entropy Modeling for Learned Image Compression
Wei Jiang, Jiayu Yang, Yongqi Zhai +2
The latent representation in learned image compression encompasses channel-wise, local spatial, and global spatial correlations, which are essential for the entropy model to captur…
DeepFGS: Fine-Grained Scalable Coding for Learned Image Compression
Yi Ma, Yongqi Zhai, Ronggang Wang
Scalable coding, which can adapt to channel bandwidth variation, performs well in today's complex network environment. However, the existing scalable compression methods face two c…