部分期刊论文
2. Taoyu Yang, Zengjie Tan, Yuanyuan Xu*, and Shuwen Cai, “Collaborative Edge Caching and Transcoding for 360-Degree Video Streaming Based on Deep Reinforcement Learning”, IEEE Internet of Things Journal, vol. 9, no. 24, pp. 25551-25564, 15 Dec. 2022, doi: 10.1109/JIOT.2022.3197798. (IF 10.238)
3. Kun Zhu, Yuanyuan Xu*, Jun Qian, and Dusit Niyato, “Revenue Optimal Auction For Resource Allocation in Wireless Virtualization: A Deep Learning Approach, IEEE Trans. on Mobile Computing, vol. 21, no. 4, pp. 1374-1387, 1 April 2022. (CCF A,IF 5.112,中科院2区).
4. Kun Zhu, Lujiu Li, Yuanyuan Xu*, Tong Zhang, Lu Zhou, “Multi-Connection Based Scalable Video Streaming in UDNs: A Multi-Agent Multi-Armed Bandit Approach”, IEEE Trans. on Wireless Communications, vol. 21, no. 2, pp. 1156-1169, Feb. 2022. (CCF B,IF 6.779,中科院1区)
5. Xiang Zhang*, Ce Zhu, Honggang Wu, Zhi Liu, and Yuangyuan Xu, “An imbalance compensation framework for background subtraction”, IEEE Tran. on Multimedia, vol. 19, no. 11. pp. 2425-2438, Nov. 2017. (CCF-B,中信所二区,JCR一区)
6. Yuanyuan Xu, Ce Zhu*, “End-to-End Rate-Distortion Optimized Description Generation for H.264 Multiple Description Video Coding”, IEEE Trans. on Circuits and Systems for Video Technology, vol.23, no.9, pp.1523-1536, Sept. 2013. (CCF-B, 中信所一区,JCR一区)
部分会议论文
1. Xi Gu, Yuanyuan Xu*, Kun Zhu, “Semantic Importance-Based Deep Image Compression Using A Generative Approach, in Proc. of 30th International Conference on Multimedia Modeling (MMM), Jan. 29-Feb.2, 2024, Amsterdam, Netherlands.
2. Hui Chen, Yuanyuan Xu*, “Video Coding for Machines Based on Motion Assisted Saliency Analysis”, in Proc. of International Conference on Image and Graphics (ICIG 2023), Sept. 22-24. 2023, Nanjing, China.
3. Yuanyuan Xu*, Haolun Lan, “Image Compression for Machines Using Boundary-Enhanced Saliency”, in Proc. of ACM Multimedia Asia (MM Asia), Dec. 13-16, 2022, Tokyo, Japan.
4. Haoxuan Xiong, Yuanyuan Xu*, “Saliency-Guided Learned Image Compression for Object Detection”, in Proc. of 29th International Conference on Neural Information Processing (ICONIP), Nov. 22-26, 2022, New Delhi, India.
5. Shuwen Cai, Yuanyuan Xu*, “A Multi-objective Optimization Approach to Resource Allocation for Edge-Based Digital Twin, in Proc. of IEEE Global Communications Conference (GLOBECOM), Dec. 4-8, 2022, Rio de Janeiro, Brazil.
6. Yuanyuan Xu*, Taoyu Yang, Zengjie Tan, and Haolun Lan, “Fov-based Coding Optimization for 360-degree Virtual Reality Videos”,in Proc. of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 22-27, 2022. Singapore. (CCF-B)
专利:
1. 一种基于视图缩放的全景图像空洞填充方法,ZL 202110704555.4, 徐媛媛、朱雷,授权日期2022.11.11
2. 一种基于深度强化学习的全景视频边缘协作缓存替换方法,ZL 202110515718.4,谭增洁、徐媛媛、叶保留,授权日期2022.09.30
3. 一种基于用户视场的全景视频编码优化算法,ZL 202110684088.3,杨桃雨、徐媛媛、叶保留,授权日期2022.06.17
4. 一种复杂度自适应的虚拟现实设备的屏幕内容编码算法,ZL 201811139188.2,徐媛媛,授权日期2022.01.28
5. 一种基于显著性的HEVC多描述图像编码算法,ZL 2017110335768.8,徐媛媛, ,授权日期2021.07.09
6. 一种全景视频的多描述视频编码方法,ZL 201711037017.4,徐媛媛,授权日期2021.03.19
7. 一种多描述屏幕内容视频编码方法,ZL 201610958863.9,徐媛媛,授权日期 2019.05.28
8. 一种三描述格型矢量量化预测边路解码方法, ZL 201611061314.8,徐媛媛,授权日期2019.03.29
9. 一种针对虚拟现实头戴式显示设备的屏幕内容视频编码算法,ZL 201711042343.4 ,徐媛媛,授权日期 2019.03.12
个人主页:https://yyxu2019.github.io/