[21] Goh, G., Cammarata, N., Voss, C., Carter, S., Petrov, M., Schubert, L., Radford, A., and Olah, C. Multimodal neurons in artificial neural networks. Distill, 6(3):e30, 2021. 1, 5
[22] Gupta, A., Dollar, P., and Girshick, R. Lvis: A dataset for large vocabulary instance segmentation. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp. 5356-5364, 2019. 34
[23] He, K., Zhang, X., Ren, S., and Sun, J. Deep residual learning for image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 770-778, 2016. 1, 2, 3, 7, 25, 27, 69
[24] Hendrycks, D. and Dietterich, T. Benchmarking neural network robustness to common corruptions and perturbations. arXiv preprint arXiv:1903.12261, 2019. 7, 8
[25] Hendrycks, D., Mu, N., Cubuk, E. D., Zoph, B., Gilmer, J., and Lakshminarayanan, B. Augmix: A simple data processing method to improve robustness and uncertainty. arXiv preprint arXiv:1912.02781, 2019. 6, 53
[26] Hendrycks, D., Basart, S., Mu, N., Kadavath, S., Wang, F., Dorundo, E., Desai, R., Zhu, T., Parajuli, S., Guo, M., et al. The many faces of robustness: A critical analysis of out-of-distribution generalization. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 8340-8349, 2021. 3, 6, 7, 27, 36, 69
[27] Hendrycks, D., Zhao, K., Basart, S., Steinhardt, J., and Song, D. Natural adversarial examples. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 15262-15271, 2021. 2, 3, 7
[28] Howard, A., Sandler, M., Chu, G., Chen, L.-C., Chen, B., Tan, M., Wang, W., Zhu, Y., Pang, R., Vasudevan, V., et al. Searching for mobilenetv3. In Proceedings of the IEEE/CVF international conference on computer vision, pp. 1314-1324, 2019. 27, 65
[29] Huang, G., Liu, Z., Van Der Maaten, L., and Weinberger, K. Q. Densely connected convolutional networks. In Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 4700-4708, 2017. 27
[30] Ilharco, G., Wortsman, M., Wightman, R., Gordon, C., Carlini, N., Taori, R., Dave, A., Shankar, V., Namkoong, H., Miller, J., Hajishirzi, H., Farhadi, A., and Schmidt, L. Openclip, July 2021. URL https://doi.org/10.5281/zenodo.5143773. If you use this software, please cite it as below. 8
[31] Jaderberg, M., Simonyan, K., Zisserman, A., et al. Spatial transformer networks. Advances in neural information processing systems, 28, 2015. 2, 3
[32] Jin, C., Tanno, R., Mertzanidou, T., Panagiotaki, E., and Alexander, D. C. Learning to downsample for segmentation of ultra-high resolution images. arXiv preprint arXiv:2109.11071, 2021. 2, 3
[33] Kang, M., Zhu, J.-Y., Zhang, R., Park, J., Shechtman, E., Paris, S., and Park, T. Scaling up gans for text-to-image synthesis. arXiv preprint arXiv:2303.05511, 2, 2023. 8, 9
[34] Kim, I., Kim, Y., and Kim, S. Learning loss for test-time augmentation. Advances in Neural Information Processing Systems, 33:4163-4174, 2020. 3
[35] Kleinberg, J. and Tardos, E. Algorithm Design. Addison-Wesley Longman Publishing Co., Inc., USA, 2005. ISBN 0321295358. 5, 22
[36] Kong, F. and Henao, R. Efficient classification of very large images with tiny objects. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 2384-2394, 2022. 2, 3
[37] Krause, J., Jin, H., Yang, J., and Fei-Fei, L. Fine-grained recognition without part annotations. In Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 5546-5555, 2015. 2, 3
[38] Krizhevsky, A., Sutskever, I., and Hinton, G. E. Imagenet classification with deep convolutional neural networks. Advances in neural information processing systems, 25, 2012. 1, 3, 5, 10, 25, 26, 27
[39] Leung, B., Ho, C.-H., Persekian, A., Orozco, D., Chang, Y., Sandstrom, E., Liu, B., and Vasconcelos, N. Oowl500: Overcoming dataset collection bias in the wild. arXiv preprint arXiv:2108.10992, 2021. 3
[40] Li, B., Wu, F., Lim, S.-N., Belongie, S., and Weinberger, K. Q. On feature normalization and data augmentation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 12383-12392, 2021. 7, 27, 36, 69