| Revisiting unreasonable effectiveness of data in deep learning era C Sun, A Shrivastava, S Singh, A Gupta Proceedings of the IEEE international conference on computer vision, 843-852, 2017 | 3141 | 2017 |
| Variational image compression with a scale hyperprior J Ballé, D Minnen, S Singh, SJ Hwang, N Johnston arXiv preprint arXiv:1802.01436, 2018 | 1926 | 2018 |
| What makes Paris look like Paris? C Doersch, S Singh, A Gupta, J Sivic, AA Efros Communications of the ACM 58 (12), 103-110, 2015 | 1023 | 2015 |
| No fuss distance metric learning using proxies Y Movshovitz-Attias, A Toshev, TK Leung, S Ioffe, S Singh Proceedings of the IEEE International Conference on Computer Vision, 360-368, 2017 | 792 | 2017 |
| Unsupervised Discovery of Mid-Level Discriminative Patches S Singh, A Gupta, AA Efros Arxiv preprint arXiv:1205.3137, 2012 | 750 | 2012 |
| Where to look: Focus regions for visual question answering KJ Shih, S Singh, D Hoiem Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 594 | 2016 |
| Improved lossy image compression with priming and spatially adaptive bit rates for recurrent networks N Johnston, D Vincent, D Minnen, M Covell, S Singh, T Chinen, ... Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 464 | 2018 |
| Channel-Wise Autoregressive Entropy Models for Learned Image Compression D Minnen, S Singh Proc. of IEEE Int. Conf. on Image Processing ICIP, 2020 | 382 | 2020 |
| Nonlinear transform coding J Ballé, PA Chou, D Minnen, S Singh, N Johnston, E Agustsson, ... IEEE Journal of Selected Topics in Signal Processing 15 (2), 339-353, 2020 | 219 | 2020 |
| Swapout: Learning an ensemble of deep architectures S Singh, D Hoiem, D Forsyth Advances in Neural Information Processing Systems, 1696-1704, 2016 | 186 | 2016 |
| Filter response normalization layer: Eliminating batch dependence in the training of deep neural networks S Singh, S Krishnan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 168 | 2020 |
| Constrained Semi-Supervised Learning Using Attributes and Comparative Attributes A Shrivastava, S Singh, A Gupta Computer Vision–ECCV 2012, 369-383, 2012 | 126 | 2012 |
| End-to-end Learning of Compressible Features S Singh, S Abu-El-Haija, N Johnston, J Ballé, A Shrivastava, G Toderici 2020 IEEE International Conference on Image Processing (ICIP), 3349-3353, 2020 | 78 | 2020 |
| Spatially adaptive image compression using a tiled deep network D Minnen, G Toderici, M Covell, T Chinen, N Johnston, J Shor, SJ Hwang, ... 2017 IEEE International Conference on Image Processing (ICIP), 2796-2800, 2017 | 72 | 2017 |
| Part localization using multi-proposal consensus for fine-grained categorization KJ Shih, A Mallya, S Singh, D Hoiem arXiv preprint arXiv:1507.06332, 2015 | 61 | 2015 |
| Evalnorm: Estimating batch normalization statistics for evaluation S Singh, A Shrivastava Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 60 | 2019 |
| Deep Implicit Volume Compression D Tang, S Singh, PA Chou, C Hane, M Dou, S Fanello, J Taylor, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 49 | 2020 |
| Scalable Model Compression by Entropy Penalized Reparameterization D Oktay, J Ballé, S Singh, A Shrivastava arXiv preprint arXiv:1906.06624, 2019 | 48 | 2019 |
| Image-Dependent Local Entropy Models for Learned Image Compression D Minnen, G Toderici, S Singh, SJ Hwang, M Covell 2018 25th IEEE International Conference on Image Processing (ICIP), 430-434, 2018 | 43 | 2018 |
| 3d scene compression through entropy penalized neural representation functions T Bird, J Ballé, S Singh, PA Chou 2021 Picture Coding Symposium (PCS), 1-5, 2021 | 33 | 2021 |
David MinnenGoogle在 google.com 的電子郵件地址已通過驗證
