• I am a Ph.D. candidate in Department of Electronic and Computer Engineering (ECE) at Hong Kong University of Science and Technology (HKUST), supervised by Prof. Jun Zhang. I received my B.Eng in School of Electronic Information and Enginnering from South China University of Science and Technology (SCUT) in 2021.
• My research interests lie in Gaussian Splatting, implicit neural representation, image/video compression, image/video coding for machine, low-level vision, and edge AI.

💥 💥 I am currently seeking internship and full-time job opportunities. If you are interested in my profile, please do not hesitate to contact me. 💥 💥

🔥 News

• [Mar., 2024] Our paper “GaussianImage: 1000 FPS Image Representation and Compression by 2D Gaussian Splatting” was submitted. [Paper]
• [Mar., 2024] Our paper “Content-aware Masked Image Modeling Transformer for Stereo Image Compression” was submitted. [Paper]
• [Feb., 2024] Our paper “Boosting Neural Representations for Videos with a Conditional Decoder” was accepted to CVPR 2024 Highlight. [Paper]
• [Feb., 2024] Our paper “Controlling Encoder of Deep Video Compression for Machine” was accepted to CVPR 2024. [Paper]
• [Dec., 2023] Our paper “Large language models empowered autonomous edge AI for connected intelligence” was accepted to IEEE Communications Magazine. [Paper]
• [Sep., 2023] Our paper “Task-oriented communication for edge video analytics” was accepted to IEEE Transactions on Wireless Communications. [Paper]
• [Mar., 2023] Our paper “Low-complexity Deep Video Compression with A Distributed Coding Architecture” was accepted to ICME 2023. [Paper]
• [Jan., 2023] Our paper “LDMIC: Learning-based distributed multi-view image coding” was accepted to ICLR 2023. [Paper]

📝 Selected Publications

Refer to my Google Scholar Profile for full publication list.

• Implicit Neural Representation:
  • X. Zhang, R. Yang, D. He, X. Ge, T. Xu, Y. Wang, H. Qin, and J. Zhang, “Boosting Neural Representations for Videos with a Conditional Decoder,” IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, USA, June 2024. [Paper] (Highlight)
• Image and video compression:
  • X. Ge, J. Luo, X. Zhang, T. Xu, G. Lu, D. He, J. Geng, Y. Wang, J. Zhang, and H. Qin, “Controlling encoder of deep video compression for machine,” IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, USA, Jun. 2024. [Paper]
  • X. Zhang, J. Shao, and J. Zhang, “Low-complexity Deep Video Compression with A Distributed Coding Architecture,” IEEE International Conference on Multimedia and Expo (ICME), Brisbane, Australia, July 2023. [Paper] [Code]
  • X. Zhang, J. Shao, and J. Zhang, “LDMIC: Learning-based distributed multi-view image coding,” International Conference on Learning Representations (ICLR), Kigali, Rwanda, May 2023. [Paper] [Code]
• Edge AI:
  • Y. Shen, J. Shao, X. Zhang, Z. Lin, H. Pan, D. Li, J. Zhang, K. B. Letaief, “Large language models empowered autonomous edge AI for connected intelligence,” IEEE Commun. Mag., to appear. [Paper]
  • J. Shao, X. Zhang, and J. Zhang, “Task-oriented communication for edge video analytics,” IEEE Trans. Wireless Commun., to appear. [Paper]
  • X. Zhang, J. Shao, Y. Mao, and J. Zhang, “Communication-Computation Efficient Device-Edge Co-Inference via AutoML,” IEEE Global Communications Conference (GLOBECOM), Madrid, Spain, December 2021. [Paper]

🎖 Selected Awards

• Hong Kong Postgraduate Scholarship, 2021-2025.
• National Scholarship, 2018-2019.