| Learned image compression with gaussian-laplacian-logistic mixture model and concatenated residual modules H Fu, F Liang, J Lin, B Li, M Akbari, J Liang, G Zhang, D Liu, C Tu, J Han IEEE Transactions on Image Processing 32, 2063-2076, 2023 | 37* | 2023 |
| Improved hybrid layered image compression using deep learning and traditional codecs H Fu, F Liang, B Lei, N Bian, Q Zhang, M Akbari, J Liang, C Tu Signal Processing: Image Communication 82, 115774, 2020 | 24 | 2020 |
| Variable-rate multi-frequency image compression using modulated generalized octave convolution J Lin, M Akbari, H Fu, Q Zhang, S Wang, J Liang, D Liu, F Liang, G Zhang, ... 2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP …, 2020 | 18 | 2020 |
| An extended hybrid image compression based on soft-to-hard quantification H Fu, F Liang, B Lei IEEE Access 8, 95832-95842, 2020 | 13 | 2020 |
| Asymmetric learned image compression with multi-scale residual block, importance scaling, and post-quantization filtering H Fu, F Liang, J Liang, B Li, G Zhang, J Han IEEE Transactions on Circuits and Systems for Video Technology, 2023 | 11 | 2023 |
| A high-performance and low-cost montgomery modular multiplication based on redundant binary representation B Li, J Wang, G Ding, H Fu, B Lei, H Yang, J Bi, S Lei IEEE Transactions on Circuits and Systems II: Express Briefs 68 (7), 2660-2664, 2021 | 11 | 2021 |
| An extended context-based entropy hybrid modeling for image compression H Fu, F Liang, B Lei, Q Zhang, J Liang, C Tu, G Zhang Signal Processing: Image Communication 95, 116244, 2021 | 8 | 2021 |
| Learned image compression with generalized octave convolution and cross-resolution parameter estimation H Fu, F Liang Signal Processing 202, 108778, 2023 | 7 | 2023 |
| A deep image compression framework for face recognition N Bian, F Liang, H Fu, B Lei 2019 2nd China Symposium on Cognitive Computing and Hybrid Intelligence …, 2019 | 7 | 2019 |
| Learned variable-rate multi-frequency image compression using modulated generalized octave convolution J Lin, M Akbari, H Fu, Q Zhang, S Wang, J Liang, D Liu, F Liang, G Zhang, ... arXiv preprint arXiv:2009.13074, 2020 | 6 | 2020 |
| A deep image compression framework for face recognition finding the optimum structure of CNN for face recognition N Bian, F Liang, H Fu, B Lei IEEE 19 (31.00), 2019 | 5 | 2019 |
| ROI-Based Deep Image Compression with Swin Transformers B Li, J Liang, H Fu, J Han ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 4 | 2023 |
| An end-to-end face compression and recognition framework based on entropy coding model B Lei, F Liang, H Fu 2021 IEEE 6th International Conference on Cloud Computing and Big Data …, 2021 | 2 | 2021 |
| Fast and High-Performance Learned Image Compression With Improved Checkerboard Context Model, Deformable Residual Module, and Knowledge Distillation H Fu, F Liang, J Liang, Y Wang, G Zhang, J Han arXiv preprint arXiv:2309.02529, 2023 | 1 | 2023 |
| Efficient Learned Image Compression with Selective Kernel Residual Module and Channel-Wise Causal Context Model H Fu, F Liang, J Liang, Z Fang, G Zhang, J Han ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | | 2024 |
| S2LIC: Learned Image Compression with the SwinV2 Block, Adaptive Channel-wise and Global-inter Attention Context Y Wang, F Liang, J Liang, H Fu arXiv preprint arXiv:2403.14471, 2024 | | 2024 |
| Learned Image Compression with Dual-Branch Encoder and Conditional Information Coding H Fu, F Liang, J Liang, Z Fang, G Zhang, J Han arXiv preprint arXiv:2401.11093, 2024 | | 2024 |
| Enhanced Residual SwinV2 Transformer for Learned Image Compression Y Wang, F Liang, H Fu, J Liang, H Qin, J Liang arXiv preprint arXiv:2308.11864, 2023 | | 2023 |
| Learned Image Compression with Inception Residual Blocks and Multi-Scale Attention Module H Fu, F Liang, J Liang, BL Li, GH Zhang, JN Han 2022 Picture Coding Symposium (PCS), 43-47, 2022 | | 2022 |
Jie LiangProfessor, School of Engineering Science, Simon Fraser University. Fellow of CAEVerified email at sfu.ca
