4 papers
AUHead: Realistic Emotional Talking Head Generation via Action Units Control
Jiayi Lyu, Leigang Qu, Wenjing Zhang +6
Realistic talking-head video generation is critical for virtual avatars, film production, and interactive systems. Current methods struggle with nuanced emotional expressions due t…
In-Context Learning for Deep Joint Source-Channel Coding Over MIMO Channels
Meng Hua, Wenjing Zhang, Chenghong Bian +1
Large language models have demonstrated the ability to perform \textit{in-context learning} (ICL), whereby the model performs predictions by directly mapping the query and a few ex…
Compression Beyond Pixels: Semantic Compression with Multimodal Foundation Models
Ruiqi Shen, Haotian Wu, Wenjing Zhang +2
Recent deep learning-based methods for lossy image compression achieve competitive rate-distortion performance through extensive end-to-end training and advanced architectures. How…
Zero-Shot Semantic Communication with Multimodal Foundation Models
Jiangjing Hu, Haotian Wu, Wenjing Zhang +4
Most existing semantic communication (SemCom) systems use deep joint source-channel coding (DeepJSCC) to encode task-specific semantics in a goal-oriented manner. However, their re…