| Deep convolutional neural network for decompressed video enhancement R Lin, Y Zhang, H Wang, X Wang, Q Dai 2016 Data Compression Conference (DCC), 617-617, 2016 | 13 | 2016 |
| Beyond keypoint coding: Temporal evolution inference with compact feature representation for talking face video compression B Chen, Z Wang, B Li, R Lin, S Wang, Y Ye 2022 Data Compression Conference (DCC), 13-22, 2022 | 12 | 2022 |
| Deep video compression for P-frame in sub-sampled color spaces R Lin, P Zhang, M Wang, S Wang, S Kwong 2022 IEEE International Symposium on Circuits and Systems (ISCAS), 3200-3204, 2022 | 5 | 2022 |
| Learning-based compression for noisy images in the wild P Zhang, M Wang, B Chen, R Lin, X Wang, S Wang, S Kwong IEEE Transactions on Circuits and Systems for Video Technology, 2022 | 3 | 2022 |
| Multiple hypotheses based motion compensation for learned video compression R Lin, M Wang, P Zhang, S Wang, S Kwong Neurocomputing 548, 126396, 2023 | 2 | 2023 |
| Towards modality transferable visual information representation with optimal model compression R Lin, L Zhu, S Wang, S Kwong Proceedings of the 28th ACM International Conference on Multimedia, 3705-3714, 2020 | 2 | 2020 |
| System and Method for Facilitating Machine-Learning Based Media Compression (Filed) S KWONG, R LIN, S WANG | | 2022 |
| Depth Map Upsampling via Progressive Manner Based on Probability Maximization R Lin, Y Zhang, H Wang, X Wang, Q Dai Pacific Rim Conference on Multimedia, 84-93, 2015 | | 2015 |
| Multiple Hypotheses Based Motion Compensation for Learned Video S Kwong, R Lin, M Wang, P Zhang, S Wang Available at SSRN 4342103, 0 | | |
Yongbing ZhangHarbin Institute of Technology (Shenzhen)Verified email at hit.edu.cn
