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| Aod-net: All-in-one dehazing network B Li, X Peng, Z Wang, J Xu, D Feng Proceedings of the IEEE international conference on computer vision, 4770-4778, 2017 | 1913 | 2017 |
| Graph Contrastive Learning with Augmentations Y You, T Chen, Y Sui, T Chen, Z Wang, Y Shen Advances in Neural Information Processing Systems (NeurIPS), 2020 | 1810 | 2020 |
| Benchmarking single-image dehazing and beyond B Li, W Ren, D Fu, D Tao, D Feng, W Zeng, Z Wang IEEE Transactions on Image Processing 28 (1), 492-505, 2018 | 1673 | 2018 |
| EnlightenGAN: Deep light enhancement without paired supervision Y Jiang, X Gong, D Liu, Y Cheng, C Fang, X Shen, J Yang, P Zhou, ... IEEE Transactions on Image Processing (TIP), 2020 | 1527 | 2020 |
| Unitbox: An advanced object detection network J Yu, Y Jiang, Z Wang, Z Cao, T Huang Proceedings of the 24th ACM international conference on Multimedia, 516-520, 2016 | 1515 | 2016 |
| DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better O Kupyn, T Martyniuk, J Wu, Z Wang IEEE International Conference on Computer Vision (ICCV), 2019 | 1006 | 2019 |
| TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can Scale Up Y Jiang, S Chang, Z Wang Thirty-Fifth Conference on Neural Information Processing Systems, 2021 | 625* | 2021 |
| ABD-Net: Attentive but Diverse Person Re-Identification T Chen, S Ding, J Xie, Y Yuan, W Chen, Y Yang, Z Ren, Z Wang IEEE International Conference on Computer Vision (ICCV), 2019 | 594 | 2019 |
| DeepAffinity: interpretable deep learning of compound–protein affinity through unified recurrent and convolutional neural networks M Karimi, D Wu, Z Wang, Y Shen Bioinformatics 35 (18), 3329-3338, 2019 | 427 | 2019 |
| Graph Contrastive Learning Automated Y You, T Chen, Y Shen, Z Wang International Conference on Machine Learning (ICML), 2021 | 423 | 2021 |
| Plug-and-Play Methods Provably Converge with Properly Trained Denoisers EK Ryu, J Liu, S Wang, X Chen, Z Wang, W Yin International Conference on Machine Learning (ICML), 2019 | 364 | 2019 |
| The lottery ticket hypothesis for pre-trained bert networks T Chen, J Frankle, S Chang, S Liu, Y Zhang, Z Wang, M Carbin Advances in Neural Information Processing Systems (NeurIPS), 2020 | 355 | 2020 |
| Can we gain more from orthogonality regularizations in training deep networks? N Bansal, X Chen, Z Wang Advances in Neural Information Processing Systems 31, 2018 | 347 | 2018 |
| AutoGAN: Neural architecture search for generative adversarial networks X Gong, S Chang, Y Jiang, Z Wang Proceedings of the IEEE International Conference on Computer Vision, 3224-3234, 2019 | 339 | 2019 |
| Single Image Deraining: A Comprehensive Benchmark Analysis S Li, IB Araujo, W Ren, Z Wang, EK Tokuda, RH Junior, R Cesar-Junior, ... IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 | 323 | 2019 |
| Studying very low resolution recognition using deep networks Z Wang, S Chang, Y Yang, D Liu, TS Huang Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 293 | 2016 |
| Text2video-zero: Text-to-image diffusion models are zero-shot video generators L Khachatryan, A Movsisyan, V Tadevosyan, R Henschel, Z Wang, ... Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023 | 284 | 2023 |
| Robust video super-resolution with learned temporal dynamics D Liu, Z Wang, Y Fan, X Liu, Z Wang, S Chang, T Huang Proceedings of the IEEE International Conference on Computer Vision, 2507-2515, 2017 | 270 | 2017 |
| Drawing early-bird tickets: Towards more efficient training of deep networks H You, C Li, P Xu, Y Fu, Y Wang, X Chen, Y Lin, Z Wang, RG Baraniuk International Conference on Learning Representation (ICLR), 2020 | 259 | 2020 |
Shiyu ChangUniversity of California, Santa Barbara在 cs.ucsb.edu 的电子邮件经过验证
