| Cvt: Introducing convolutions to vision transformers H Wu, B Xiao, N Codella, M Liu, X Dai, L Yuan, L Zhang Proceedings of the IEEE/CVF international conference on computer vision, 22-31, 2021 | 2435 | 2021 |
| Dynamic convolution: Attention over convolution kernels Y Chen, X Dai, M Liu, D Chen, L Yuan, Z Liu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 1206 | 2020 |
| Florence: A new foundation model for computer vision L Yuan, D Chen, YL Chen, N Codella, X Dai, J Gao, H Hu, X Huang, B Li, ... arXiv preprint arXiv:2111.11432, 2021 | 950 | 2021 |
| Phi-3 technical report: A highly capable language model locally on your phone M Abdin, J Aneja, H Awadalla, A Awadallah, AA Awan, N Bach, A Bahree, ... arXiv preprint arXiv:2404.14219, 2024 | 844 | 2024 |
| Dynamic head: Unifying object detection heads with attentions X Dai, Y Chen, B Xiao, D Chen, M Liu, L Yuan, L Zhang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 780 | 2021 |
| Mobile-former: Bridging mobilenet and transformer Y Chen, X Dai, D Chen, M Liu, X Dong, L Yuan, Z Liu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 631 | 2022 |
| Towards better analysis of deep convolutional neural networks M Liu, J Shi, Z Li, C Li, J Zhu, S Liu IEEE transactions on visualization and computer graphics 23 (1), 91-100, 2016 | 622 | 2016 |
| A survey on information visualization: recent advances and challenges S Liu, W Cui, Y Wu, M Liu The Visual Computer 30, 1373-1393, 2014 | 521 | 2014 |
| Towards better analysis of machine learning models: A visual analytics perspective S Liu, X Wang, M Liu, J Zhu Visual Informatics 1 (1), 48-56, 2017 | 461 | 2017 |
| Storyflow: Tracking the evolution of stories S Liu, Y Wu, E Wei, M Liu, Y Liu IEEE Transactions on Visualization and Computer Graphics 19 (12), 2436-2445, 2013 | 286 | 2013 |
| Tinyvit: Fast pretraining distillation for small vision transformers K Wu, J Zhang, H Peng, M Liu, B Xiao, J Fu, L Yuan European conference on computer vision, 68-85, 2022 | 274 | 2022 |
| Bevt: Bert pretraining of video transformers R Wang, D Chen, Z Wu, Y Chen, X Dai, M Liu, YG Jiang, L Zhou, L Yuan Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 264 | 2022 |
| A survey of visual analytics techniques for machine learning J Yuan, C Chen, W Yang, M Liu, J Xia, S Liu Computational Visual Media 7, 3-36, 2021 | 247 | 2021 |
| Opinionflow: Visual analysis of opinion diffusion on social media Y Wu, S Liu, K Yan, M Liu, F Wu IEEE transactions on visualization and computer graphics 20 (12), 1763-1772, 2014 | 244 | 2014 |
| Dynamic relu Y Chen, X Dai, M Liu, D Chen, L Yuan, Z Liu European conference on computer vision, 351-367, 2020 | 241 | 2020 |
| Analyzing the training processes of deep generative models M Liu, J Shi, K Cao, J Zhu, S Liu IEEE transactions on visualization and computer graphics 24 (1), 77-87, 2017 | 191 | 2017 |
| Minivit: Compressing vision transformers with weight multiplexing J Zhang, H Peng, K Wu, M Liu, B Xiao, J Fu, L Yuan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 146 | 2022 |
| Masked video distillation: Rethinking masked feature modeling for self-supervised video representation learning R Wang, D Chen, Z Wu, Y Chen, X Dai, M Liu, L Yuan, YG Jiang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 101 | 2023 |
| Reduce information loss in transformers for pluralistic image inpainting Q Liu, Z Tan, D Chen, Q Chu, X Dai, Y Chen, M Liu, L Yuan, N Yu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 101 | 2022 |
| Micronet: Improving image recognition with extremely low flops Y Li, Y Chen, X Dai, D Chen, M Liu, L Yuan, Z Liu, L Zhang, ... Proceedings of the IEEE/CVF International conference on computer vision, 468-477, 2021 | 90 | 2021 |
Xiyang DaiMicrosoftE-mailová adresa ověřena na: microsoft.com