Prompting in Vision
Uncovering the Hidden Cost of Model Compression-
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[supp]
[arXiv]
[bibtex]@InProceedings{Misra_2024_CVPR, author = {Misra, Diganta and Chaudhary, Muawiz and Goyal, Agam and Runwal, Bharat and Chen, Pin Yu}, title = {Uncovering the Hidden Cost of Model Compression}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {1611-1621} }
AAPL: Adding Attributes to Prompt Learning for Vision-Language Models-
[pdf]
[arXiv]
[bibtex]@InProceedings{Kim_2024_CVPR, author = {Kim, Gahyeon and Kim, Sohee and Lee, Seokju}, title = {AAPL: Adding Attributes to Prompt Learning for Vision-Language Models}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {1572-1582} }
What Makes Multimodal In-Context Learning Work?-
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[supp]
[arXiv]
[bibtex]@InProceedings{Baldassini_2024_CVPR, author = {Baldassini, Folco Bertini and Shukor, Mustafa and Cord, Matthieu and Soulier, Laure and Piwowarski, Benjamin}, title = {What Makes Multimodal In-Context Learning Work?}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {1539-1550} }
Low-Rank Few-Shot Adaptation of Vision-Language Models-
[pdf]
[supp]
[arXiv]
[bibtex]@InProceedings{Zanella_2024_CVPR, author = {Zanella, Maxime and Ben Ayed, Ismail}, title = {Low-Rank Few-Shot Adaptation of Vision-Language Models}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {1593-1603} }
Enhancing Visual Question Answering through Question-Driven Image Captions as Prompts-
[pdf]
[bibtex]@InProceedings{Ozdemir_2024_CVPR, author = {\"Ozdemir, \"Ovg\"u and Akag\"und\"uz, Erdem}, title = {Enhancing Visual Question Answering through Question-Driven Image Captions as Prompts}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {1562-1571} }
Conv-Adapter: Exploring Parameter Efficient Transfer Learning for ConvNets-
[pdf]
[supp]
[bibtex]@InProceedings{Chen_2024_CVPR, author = {Chen, Hao and Tao, Ran and Zhang, Han and Wang, Yidong and Li, Xiang and Ye, Wei and Wang, Jindong and Hu, Guosheng and Savvides, Marios}, title = {Conv-Adapter: Exploring Parameter Efficient Transfer Learning for ConvNets}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {1551-1561} }
Prompting Foundational Models for Omni-supervised Instance Segmentation-
[pdf]
[bibtex]@InProceedings{Das_2024_CVPR, author = {Das, Arnav M. and Chaudhry, Ritwick and Kundu, Kaustav and Modolo, Davide}, title = {Prompting Foundational Models for Omni-supervised Instance Segmentation}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {1583-1592} }
PointPrompt: A Multi-modal Prompting Dataset for Segment Anything Model-
[pdf]
[bibtex]@InProceedings{Quesada_2024_CVPR, author = {Quesada, Jorge and Alotaibi, Mohammad and Prabhushankar, Mohit and Alregib, Ghassan}, title = {PointPrompt: A Multi-modal Prompting Dataset for Segment Anything Model}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {1604-1610} }