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Recently, CLIP has found practical utility in the domain of pixel-level zero-shot segmentation tasks.
Context-aware feature generation for zero-shot semantic segmentation
Gu, Z.; Zhou, S.; Niu, L.; Zhao, Z.; and Zhang, L. 2020 · 1929
Earlier work this paper cites.
Multiscale structural similarity for image quality assessment
Wang, Z.; Simoncelli, E. P.; and Bovik, A. C. 2003 · 2003
Earlier work this paper cites.
Focal loss for dense object detection
Lin, T.-Y.; Goyal, P.; Girshick, R.; He, K.; and Dollár, P. 2017 · 2017
Earlier work this paper cites.
Zero-shot semantic segmentation
Bucher, M.; Vu, T.-H.; Cord, M.; and Pérez, P. 2019 · 2019
Earlier work this paper cites.
Semantic projection network for zero-and few-label semantic segmentation
Xian, Y.; Choudhury, S.; He, Y.; Schiele, B.; and Akata, Z. 2019 · 2019
Earlier work this paper cites.
MMSegmentation: OpenMMLab Semantic Segmentation Toolbox and Benchmark
Contributors, M. 2020 · 2020
Earlier work this paper cites.
What Can Be Transferred: Unsupervised Domain Adaptation for Endoscopic Lesions Segmentation
Dong, J.; Cong, Y.; Sun, G.; Zhong, B.; and Xu, X. 2020 · 2020
Earlier work this paper cites.
Video object segmentation with episodic graph memory networks
Lu, X.; Wang, W.; Danelljan, M.; Zhou, T.; Shen, J.; and Van Gool, L. 2020 · 2020
Earlier work this paper cites.
Exploiting a joint embedding space for generalized zero-shot semantic segmentation
Baek, D.; Oh, Y.; and Ham, B. 2021 · 2021
Earlier work this paper cites.
Semi-supervised semantic segmentation with cross pseudo supervision
Chen, X.; Yuan, Y.; Zeng, G.; and Wang, J. 2021 · 2021
Earlier work this paper cites.
Sign: Spatial-information incorporated generative network for generalized zero-shot semantic segmentation
Cheng, J.; Nandi, S.; Natarajan, P.; and Abd-Almageed, W. 2021 · 2021
Earlier work this paper cites.
Where and How to Transfer: Knowledge Aggregation-Induced Transferability Perception for Unsupervised Domain Adaptation
Dong, J.; Cong, Y.; Sun, G.; Fang, Z.; and Ding, Z. 2021 · 2021
Earlier work this paper cites.
Clip-adapter: Better vision-language models with feature adapters
Gao, P.; Geng, S.; Zhang, R.; Ma, T.; Fang, R.; Zhang, Y.; Li, H.; and Qiao, Y. 2021 · 2021
Earlier work this paper cites.
Vln bert: A recurrent vision-and-language bert for navigation
Hong, Y.; Wu, Q.; Qi, Y.; Rodriguez-Opazo, C.; and Gould, S. 2021 · 2021
Cited alongside, same era.
Seeing out of the box: End-to-end pre-training for vision-language representation learning
Huang, Z.; Zeng, Z.; Huang, Y.; Liu, B.; Fu, D.; and Fu, J. 2021 · 2021
Cited alongside, same era.
Mdetr-modulated detection for end-to-end multi-modal understanding
Kamath, A.; Singh, M.; LeCun, Y.; Synnaeve, G.; Misra, I.; and Carion, N. 2021 · 2021
Cited alongside, same era.
Vilt: Vision-and-language transformer without convolution or region supervision
Kim, W.; Son, B.; and Kim, I. 2021 · 2021
Cited alongside, same era.
Image retrieval on real-life images with pre-trained vision-and-language models
Liu, Z.; Rodriguez-Opazo, C.; Teney, D.; and Gould, S. 2021 · 2021
Cited alongside, same era.
Segmentation in style: Unsupervised semantic image segmentation with stylegan and clip
Jiang, J.; Liu, Z.; and Zheng, N. 2022 · 2022
Later among the works it cites.
Prompt distribution learning
Lu, Y.; Liu, J.; Zhang, Y.; Liu, Y.; and Tian, X. 2022 · 2022
Later among the works it cites.
Fast Vision Transformers with HiLo Attention
Pan, Z.; Cai, J.; and Zhuang, B. 2022 · 2022
Later among the works it cites.
Denseclip: Language-guided dense prediction with context-aware prompting
Rao, Y.; Zhao, W.; Chen, G.; Tang, Y.; Zhu, Z.; Huang, G.; Zhou, J.; and Lu, J. 2022 · 2022
Later among the works it cites.
Fine-tuning image transformers using learnable memory
Sandler, M.; Zhmoginov, A.; Vladymyrov, M.; and Jackson, A. 2022 · 2022
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Cris: Clip-driven referring image segmentation
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Pakhomov, D.; Hira, S.; Wagle, N.; Green, K. E.; and Navab, N. 2021 · 2021
Cited alongside, same era.
A closer look at self-training for zero-label semantic segmentation
Pastore, G.; Cermelli, F.; Xian, Y.; Mancini, M.; Akata, Z.; and Caputo, B. 2021 · 2021
Cited alongside, same era.
Learning transferable visual models from natural language supervision
Radford, A.; Kim, J. W.; Hallacy, C.; Ramesh, A.; Goh, G.; Agarwal, S.; Sastry, G.; Askell, A.; Mishkin, P.; Clark, J.; et al. 2021 · 2021
Cited alongside, same era.
Scale-aware graph neural network for few-shot semantic segmentation
Xie, G.-S.; Liu, J.; Xiong, H.; and Shao, L. 2021 · 2021
Cited alongside, same era.
DC-net: Dual context network for 2D medical image segmentation
Xu, R.; Wang, C.; Xu, S.; Meng, W.; and Zhang, X. 2021b · 2021
Cited alongside, same era.
Decoupling zero-shot semantic segmentation
Ding, J.; Xue, N.; Xia, G.-S.; and Dai, D. 2022 · 2022
Cited alongside, same era.
Zero-shot out-of-distribution detection based on the pre-trained model clip
Esmaeilpour, S.; Liu, B.; Robertson, E.; and Shu, L. 2022 · 2022
Cited alongside, same era.
Wang, Z.; Lu, Y.; Li, Q.; Tao, X.; Guo, Y.; Gong, M.; and Liu, T. 2022 · 2022
Later among the works it cites.
Class-aware visual prompt tuning for vision-language pre-trained model
Xing, Y.; Wu, Q.; Cheng, D.; Zhang, S.; Liang, G.; and Zhang, Y. 2022 · 2022
Later among the works it cites.
Coca: Contrastive captioners are image-text foundation models
Yu, J.; Wang, Z.; Vasudevan, V.; Yeung, L.; Seyedhosseini, M.; and Wu, Y. 2022 · 2022
Later among the works it cites.
Tip-adapter: Training-free adaption of clip for few-shot classification
Zhang, R.; Zhang, W.; Fang, R.; Gao, P.; Li, K.; Dai, J.; Qiao, Y.; and Li, H. 2022 · 2022
Later among the works it cites.
Extract free dense labels from clip
Zhou, C.; Loy, C. C.; and Dai, B. 2022 · 2022
Later among the works it cites.
SpectFormer: Frequency and Attention is what you need in a Vision Transformer
Patro, B. N.; Namboodiri, V. P.; and Agneeswaran, V. S. 2023 · 2023
Closest in time.
Zegclip: Towards adapting clip for zero-shot semantic segmentation
Zhou, Z.; Lei, Y.; Zhang, B.; Liu, L.; and Liu, Y. 2023 · 2023
Closest in time.