118 citations · 177 across the 12 of their papers we have counts for
12 papers
L-LBVC: Long-Term Motion Estimation and Prediction for Learned Bi-Directional Video Compression
Yongqi Zhai, Luyang Tang, Wei Jiang +2
Recently, learned video compression (LVC) has shown superior performance under low-delay configuration. However, the performance of learned bi-directional video compression (LBVC)…
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…
Enhancing 3D Gaussian Splatting Compression via Spatial Condition-based Prediction
Jingui Ma, Yang Hu, Luyang Tang +3
Recently, 3D Gaussian Spatting (3DGS) has gained widespread attention in Novel View Synthesis (NVS) due to the remarkable real-time rendering performance. However, the substantial…
Hybrid Local-Global Context Learning for Neural Video Compression
Yongqi Zhai, Jiayu Yang, Wei Jiang +3
In neural video codecs, current state-of-the-art methods typically adopt multi-scale motion compensation to handle diverse motions. These methods estimate and compress either optic…
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…
UCVC: A Unified Contextual Video Compression Framework with Joint P-frame and B-frame Coding
Jiayu Yang, Wei Jiang, Yongqi Zhai +2
This paper presents a learned video compression method in response to video compression track of the 6th Challenge on Learned Image Compression (CLIC), at DCC 2024.Specifically, we…
TLIC: Learned Image Compression with ROI-Weighted Distortion and Bit Allocation
Wei Jiang, Yongqi Zhai, Hangyu Li +1
This short paper describes our method for the track of image compression. To achieve better perceptual quality, we use the adversarial loss to generate realistic textures, use regi…
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…
LLIC: Large Receptive Field Transform Coding with Adaptive Weights for Learned Image Compression
Wei Jiang, Peirong Ning, Jiayu Yang +3
The effective receptive field (ERF) plays an important role in transform coding, which determines how much redundancy can be removed during transform and how many spatial priors ca…
Disparity-based Stereo Image Compression with Aligned Cross-View Priors
Yongqi Zhai, Luyang Tang, Yi Ma +2
With the wide application of stereo images in various fields, the research on stereo image compression (SIC) attracts extensive attention from academia and industry. The core of SI…
MLIC: Multi-Reference Entropy Model for Learned Image Compression
Wei Jiang, Jiayu Yang, Yongqi Zhai +3
Recently, learned image compression has achieved remarkable performance. The entropy model, which estimates the distribution of the latent representation, plays a crucial role in b…
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…