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Open-vocabulary semantic segmentation requires models to effectively integrate visual representations with open-vocabulary semantic labels.
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2023
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Xu, J., Liu, S., Vahdat, A., Byeon, W., Wang, X., De Mello, S.: Open-vocabulary panoptic segmentation with text-to-image diffusion models. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 2955–2966 (2023)
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Xu, J., Hou, J., Zhang, Y., Feng, R., Wang, Y., Qiao, Y., Xie, W.: Learning open-vocabulary semantic segmentation models from natural language supervision. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 2935–2944 (2023)
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Xu, M., Zhang, Z., Wei, F., Hu, H., Bai, X.: Side adapter network for open-vocabulary semantic segmentation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 2945–2954 (2023)
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Xu, X., Xiong, T., Ding, Z., Tu, Z.: Masqclip for open-vocabulary universal image segmentation. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 887–898 (2023)
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Zou, X., Dou, Z.Y., Yang, J., Gan, Z., Li, L., Li, C., Dai, X., Behl, H., Wang, J., Yuan, L., et al.: Generalized decoding for pixel, image, and language. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 15116–15127 (2023)
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Barsellotti, L., Amoroso, R., Cornia, M., Baraldi, L., Cucchiara, R.: Training-free open-vocabulary segmentation with offline diffusion-augmented prototype generation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 3689–3698 (2024)
2024
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Lan, M., Wang, X., Ke, Y., Xu, J., Feng, L., Zhang, W.: Smooseg: smoothness prior for unsupervised semantic segmentation. Advances in Neural Information Processing Systems 36
2024
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2024
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Sun, S., Li, R., Torr, P., Gu, X., Li, S.: Clip as rnn: Segment countless visual concepts without training endeavor. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 13171–13182 (2024)
2024
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Wang, X., Li, S., Kallidromitis, K., Kato, Y., Kozuka, K., Darrell, T.: Hierarchical open-vocabulary universal image segmentation. Advances in Neural Information Processing Systems 36
2024
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Wang, Y., Sun, R., Luo, N., Pan, Y., Zhang, T.: Image-to-image matching via foundation models: A new perspective for open-vocabulary semantic segmentation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 3952–3963 (2024)
2024
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Wysoczańska, M., Ramamonjisoa, M., Trzciński, T., Siméoni, O.: Clip-diy: Clip dense inference yields open-vocabulary semantic segmentation for-free. In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. pp. 1403–1413 (2024)
2024
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