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Contrastive Language-Image Pre-training (CLIP) has made a remarkable breakthrough in open-vocabulary zero-shot image recognition.
Quattoni, A., Collins, M., Darrell, T.: Learning visual representations using images with captions. In: CVPR (2007)
2007
Earlier work this paper cites.
Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Fei-Fei, L.: Imagenet: A large-scale hierarchical image database. In: CVPR (2009)
2009
Earlier work this paper cites.
Hariharan, B., Arbeláez, P., Bourdev, L., Maji, S., Malik, J.: Semantic contours from inverse detectors. In: ICCV (2011)
2011
Earlier work this paper cites.
Lee, D.H.: Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks. In: ICMLW (2013)
2013
Earlier work this paper cites.
Dosovitskiy, A., Springenberg, J.T., Riedmiller, M., Brox, T.: Discriminative unsupervised feature learning with convolutional neural networks. In: NeurIPS (2014)
2014
Earlier work this paper cites.
Mottaghi, R., Chen, X., Liu, X., Cho, N.G., Lee, S.W., Fidler, S., Urtasun, R., Yuille, A.: The role of context for object detection and semantic segmentation in the wild. In: CVPR (2014)
2014
Earlier work this paper cites.
Yosinski, J., Clune, J., Bengio, Y., Lipson, H.: How transferable are features in deep neural networks? In: NeurIPS (2014)
2014
Earlier work this paper cites.
Chen, X., Fang, H., Lin, T.Y., Vedantam, R., Gupta, S., Dollár, P., Zitnick, C.L.: Microsoft coco captions: Data collection and evaluation server. arXiv preprint (2015)
2015
Earlier work this paper cites.
Doersch, C., Gupta, A., Efros, A.A.: Unsupervised visual representation learning by context prediction. In: ICCV (2015)
2015
Earlier work this paper cites.
Everingham, M., Eslami, S.A., Van Gool, L., Williams, C.K., Winn, J., Zisserman, A.: The pascal visual object classes challenge: A retrospective. IJCV (2015)
2015
Earlier work this paper cites.
He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: CVPR (2016)
2016
Earlier work this paper cites.
Noroozi, M., Favaro, P.: Unsupervised learning of visual representations by solving jigsaw puzzles. In: ECCV (2016)
2016
Earlier work this paper cites.
Gomez, L., Patel, Y., Rusiñol, M., Karatzas, D., Jawahar, C.: Self-supervised learning of visual features through embedding images into text topic spaces. In: CVPR (2017)
2017
Earlier work this paper cites.
Gordo, A., Larlus, D.: Beyond instance-level image retrieval: Leveraging captions to learn a global visual representation for semantic retrieval. In: CVPR (2017)
2017
Earlier work this paper cites.
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, Ł., Polosukhin, I.: Attention is all you need. In: NeurIPS (2017)
2017
Earlier work this paper cites.
Zhao, H., Puig, X., Zhou, B., Fidler, S., Torralba, A.: Open vocabulary scene parsing. In: ICCV (2017)
2017
Earlier work this paper cites.
Zhao, H., Shi, J., Qi, X., Wang, X., Jia, J.: Pyramid scene parsing network. In: CVPR (2017)
2017
Earlier work this paper cites.
Caesar, H., Uijlings, J., Ferrari, V.: Coco-stuff: Thing and stuff classes in context. In: CVPR (2018)
2018
Earlier work this paper cites.
Chen, L.C., Zhu, Y., Papandreou, G., Schroff, F., Adam, H.: Encoder-decoder with atrous separable convolution for semantic image segmentation. In: ECCV (2018)
2018
Earlier work this paper cites.
Chen, L.C., Zhu, Y., Papandreou, G., Schroff, F., Adam, H.: Encoder-decoder with atrous separable convolution for semantic image segmentation. In: ECCV (2018)
2018
Cited alongside, same era.
Hung, W.C., Tsai, Y.H., Liou, Y.T., Lin, Y.Y., Yang, M.H.: Adversarial learning for semi-supervised semantic segmentation. In: BMVC (2018)
2018
Cited alongside, same era.
Bucher, M., Vu, T.H., Cord, M., Pérez, P.: Zero-shot semantic segmentation. In: NeurIPS (2019)
2019
Cited alongside, same era.
Hendrycks, D., Dietterich, T.: Benchmarking neural network robustness to common corruptions and perturbations. In: ICLR (2019)
2019
Cited alongside, same era.
Iscen, A., Tolias, G., Avrithis, Y., Chum, O.: Label propagation for deep semi-supervised learning. In: CVPR (2019)
2019
Cited alongside, same era.
Ouali, Y., Hudelot, C., Tami, M.: Semi-supervised semantic segmentation with cross-consistency training. In: CVPR (2020)
2020
Later among the works it cites.
Sariyildiz, M.B., Perez, J., Larlus, D.: Learning visual representations with caption annotations. In: ECCV (2020)
2020
Later among the works it cites.
Chen, X., Yuan, Y., Zeng, G., Wang, J.: Semi-supervised semantic segmentation with cross pseudo supervision. In: CVPR (2021)
2021
Closest in time.
Chen, X., He, K.: Exploring simple siamese representation learning. In: CVPR (2021)
2021
Closest in time.
Desai, K., Johnson, J.: Virtex: Learning visual representations from textual annotations. In: CVPR (2021)
2021
Closest in time.
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Kato, N., Yamasaki, T., Aizawa, K.: Zero-shot semantic segmentation via variational mapping. In: ICCVW (2019)
2019
Cited alongside, same era.
Li, X., Sun, Q., Liu, Y., Zhou, Q., Zheng, S., Chua, T.S., Schiele, B.: Learning to self-train for semi-supervised few-shot classification. In: NeurIPS (2019)
2019
Cited alongside, same era.
Mittal, S., Tatarchenko, M., Brox, T.: Semi-supervised semantic segmentation with high-and low-level consistency. IEEE TPAMI (2019)
2019
Cited alongside, same era.
Xian, Y., Choudhury, S., He, Y., Schiele, B., Akata, Z.: Semantic projection network for zero-and few-label semantic segmentation. In: CVPR (2019)
2019
Cited alongside, same era.
Caron, M., Misra, I., Mairal, J., Goyal, P., Bojanowski, P., Joulin, A.: Unsupervised learning of visual features by contrasting cluster assignments. In: NeurIPS (2020)
2020
Cited alongside, same era.
Chen, L.C., Lopes, R.G., Cheng, B., Collins, M.D., Cubuk, E.D., Zoph, B., Adam, H., Shlens, J.: Naive-student: Leveraging semi-supervised learning in video sequences for urban scene segmentation. In: ECCV (2020)
2020
Cited alongside, same era.
Chen, T., Kornblith, S., Norouzi, M., Hinton, G.: A simple framework for contrastive learning of visual representations. In: ICML (2020)
2020
Cited alongside, same era.
2021
Closest in time.
Hessel, J., Holtzman, A., Forbes, M., Bras, R.L., Choi, Y.: Clipscore: A reference-free evaluation metric for image captioning. In: EMNLP (2021)
2021
Closest in time.
Jain, A., Tancik, M., Abbeel, P.: Putting nerf on a diet: Semantically consistent few-shot view synthesis. In: ICCV (2021)
2021
Closest in time.
Jia, C., Yang, Y., Xia, Y., Chen, Y.T., Parekh, Z., Pham, H., Le, Q.V., Sung, Y., Li, Z., Duerig, T.: Scaling up visual and vision-language representation learning with noisy text supervision. In: ICML (2021)
2021
Closest in time.
Pastore, G., Cermelli, F., Xian, Y., Mancini, M., Akata, Z., Caputo, B.: A closer look at self-training for zero-label semantic segmentation. In: CVPRW (2021)
2021
Closest in time.
Patashnik, O., Wu, Z., Shechtman, E., Cohen-Or, D., Lischinski, D.: Styleclip: Text-driven manipulation of stylegan imagery. In: ICCV (2021)
2021
Closest in time.
Pham, H., Dai, Z., Xie, Q., Le, Q.V.: Meta pseudo labels. In: CVPR (2021)
2021
Closest in time.
Radford, A., Kim, J.W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., Krueger, G., Sutskever, I.: Learning transferable visual models from natural language supervision. In: ICML (2021)
2021
Closest in time.
Rao, Y., Zhao, W., Chen, G., Tang, Y., Zhu, Z., Huang, G., Zhou, J., Lu, J.: Denseclip: Language-guided dense prediction with context-aware prompting. arXiv preprint (2021)
2021
Closest in time.
Ravula, S., Smyrnis, G., Jordan, M., Dimakis, A.G.: Inverse problems leveraging pre-trained contrastive representations. In: NeurIPS (2021)
2021
Closest in time.
Xie, J., Zheng, S.: Zsd-yolo: Zero-shot yolo detection using vision-language knowledge distillation. arXiv preprint (2021)
2021
Closest in time.
Yuan, X., Lin, Z., Kuen, J., Zhang, J., Wang, Y., Maire, M., Kale, A., Faieta, B.: Multimodal contrastive training for visual representation learning. In: CVPR (2021)
2021
Closest in time.
Zou, Y., Zhang, Z., Zhang, H., Li, C.L., Bian, X., Huang, J.B., Pfister, T.: Pseudoseg: Designing pseudo labels for semantic segmentation. In: ICLR (2021)
2021
Closest in time.