12 citations · 21 across the 9 of their papers we have counts for
10 papers
Video Compression with Graph-inspired Neural Representation
Changqi Wang, Ge Gao, Fan Zhang +4
Implicit Neural Representations (INR) provide a compact and content-adaptive paradigm for video compression, typically representing a video through shared network parameters and fr…
BiCRVC: An Efficient Bidirectional Neural Video Compression Framework via Coupled Representation Coding
Wei Jiang, Junru Li, Kai Zhang +1
Neural video compression (NVC) has achieved strong compression performance, but practical random-access coding still faces two technical challenges: existing bidirectional NVCs (BV…
From Noise to Latent: Generating Gaussian Latents for INR-Based Image Compression
Chaoyi Lin, Yaojun Wu, Yue Li +3
Recent implicit neural representation (INR)-based image compression methods have shown competitive performance by overfitting image-specific latent codes. However, they remain infe…
Neural Video Compression with In-Loop Contextual Filtering and Out-of-Loop Reconstruction Enhancement
Yaojun Wu, Chaoyi Lin, Yiming Wang +4
This paper explores the application of enhancement filtering techniques in neural video compression. Specifically, we categorize these techniques into in-loop contextual filtering…
BiECVC: Gated Diversification of Bidirectional Contexts for Learned Video Compression
Wei Jiang, Junru Li, Kai Zhang +1
Recent forward prediction-based learned video compression (LVC) methods have achieved impressive results, even surpassing VVC reference software VTM under the Low Delay B (LDB) con…
Releasing the Parameter Latency of Neural Representation for High-Efficiency Video Compression
Gai Zhang, Xinfeng Zhang, Lv Tang +3
For decades, video compression technology has been a prominent research area. Traditional hybrid video compression framework and end-to-end frameworks continue to explore various i…
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…
A Neural-network Enhanced Video Coding Framework beyond ECM
Yanchen Zhao, Wenxuan He, Chuanmin Jia +7
In this paper, a hybrid video compression framework is proposed that serves as a demonstrative showcase of deep learning-based approaches extending beyond the confines of tradition…
Designs and Implementations in Neural Network-based Video Coding
Yue Li, Junru Li, Chaoyi Lin +9
The past decade has witnessed the huge success of deep learning in well-known artificial intelligence applications such as face recognition, autonomous driving, and large language…