| Pruning by training: a novel deep neural network compression framework for image processing G Tian, J Chen, X Zeng, Y Liu IEEE Signal Processing Letters 28, 344-348, 2021 | 29 | 2021 |
| A Learning Framework for n-Bit Quantized Neural Networks Toward FPGAs J Chen, L Liu, Y Liu, X Zeng IEEE transactions on neural networks and learning systems 32 (3), 1067-1081, 2020 | 28 | 2020 |
| Learning spatiotemporal and motion features in a unified 2d network for action recognition M Wang, J Xing, J Su, J Chen, Y Liu IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (3), 3347-3362, 2022 | 16 | 2022 |
| Data-free quantization via mixed-precision compensation without fine-tuning J Chen, S Bai, T Huang, M Wang, G Tian, Y Liu Pattern Recognition 143, 109780, 2023 | 11 | 2023 |
| 3qnet: 3d point cloud geometry quantization compression network T Huang, J Zhang, J Chen, Z Ding, Y Tai, Z Zhang, C Wang, Y Liu ACM Transactions on Graphics (TOG) 41 (6), 1-13, 2022 | 9 | 2022 |
| Superline3d: Self-supervised line segmentation and description for lidar point cloud X Zhao, S Yang, T Huang, J Chen, T Ma, M Li, Y Liu European Conference on Computer Vision, 263-279, 2022 | 8 | 2022 |
| Adding before pruning: Sparse filter fusion for deep convolutional neural networks via auxiliary attention G Tian, Y Sun, Y Liu, X Zeng, M Wang, Y Liu, J Zhang, J Chen IEEE Transactions on Neural Networks and Learning Systems, 2021 | 8 | 2021 |
| Propagating asymptotic-estimated gradients for low bitwidth quantized neural networks J Chen, Y Liu, H Zhang, S Hou, J Yang IEEE Journal of Selected Topics in Signal Processing 14 (4), 848-859, 2020 | 6 | 2020 |
| Learning multi-agent cooperation via considering actions of teammates S Liu, W Liu, W Chen, G Tian, J Chen, Y Tong, J Cao, Y Liu IEEE Transactions on Neural Networks and Learning Systems, 2023 | 4 | 2023 |
| Learning discretized neural networks under ricci flow J Chen, H Chen, M Wang, G Dai, IW Tsang, Y Liu arXiv preprint arXiv:2302.03390, 2023 | 4 | 2023 |
| Resolution-free point cloud sampling network with data distillation T Huang, J Zhang, J Chen, Y Liu, Y Liu European Conference on Computer Vision, 54-70, 2022 | 4 | 2022 |
| Thoughts on the consistency between ricci flow and neural network behavior J Chen, T Huang, W Chen, Y Liu arXiv preprint arXiv:2111.08410, 2021 | 4 | 2021 |
| DCCD: Reducing neural network redundancy via distillation Y Liu, J Chen, Y Liu IEEE Transactions on Neural Networks and Learning Systems, 2023 | 3 | 2023 |
| Unified Data-Free Compression: Pruning and Quantization without Fine-Tuning S Bai, J Chen, X Shen, Y Qian, Y Liu Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 3 | 2023 |
| Learning to train a point cloud reconstruction network without matching T Huang, X Yang, J Zhang, J Cui, H Zou, J Chen, X Zhao, Y Liu European Conference on Computer Vision, 179-194, 2022 | 3 | 2022 |
| Towards efficient filter pruning via topology X Xu, J Chen, H Su, L Xie Journal of Real-Time Image Processing 19 (3), 639-649, 2022 | 3 | 2022 |
| Fast Point Cloud Sampling Network T Huang, J Chen, J Zhang, Y Liu, J Liang Pattern Recognition Letters 164, 216-223, 2022 | 2 | 2022 |
| M2-CLIP: A Multimodal, Multi-task Adapting Framework for Video Action Recognition M Wang, J Xing, B Jiang, J Chen, J Mei, X Zuo, G Dai, J Wang, Y Liu arXiv preprint arXiv:2401.11649, 2024 | 1 | 2024 |
| Single-shot pruning and quantization for hardware-friendly neural network acceleration B Jiang, J Chen, Y Liu Engineering Applications of Artificial Intelligence 126, 106816, 2023 | 1 | 2023 |
| Decentralized Riemannian conjugate gradient method on the Stiefel manifold J Chen, H Ye, M Wang, T Huang, G Dai, IW Tsang, Y Liu International Conference on Learning Representations, 2023 | 1 | 2023 |
Yong LiuInstitute of Cyber-Systems and Control, Zhejiang UniversityVerified email at iipc.zju.edu.cn
