L3D-IVU: 3rd Workshop on Learning with Limited Labelled Data for Image and Video Understanding
Open-world Instance Segmentation: Top-down Learning with Bottom-up Supervision-
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[arXiv]
[bibtex]@InProceedings{Kalluri_2024_CVPR, author = {Kalluri, Tarun and Wang, Weiyao and Wang, Heng and Chandraker, Manmohan and Torresani, Lorenzo and Tran, Du}, title = {Open-world Instance Segmentation: Top-down Learning with Bottom-up Supervision}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {2693-2703} }
Human-in-the-Loop Segmentation of Multi-species Coral Imagery-
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[supp]
[arXiv]
[bibtex]@InProceedings{Raine_2024_CVPR, author = {Raine, Scarlett and Marchant, Ross and Kusy, Brano and Maire, Frederic and Sunderhauf, Niko and Fischer, Tobias}, title = {Human-in-the-Loop Segmentation of Multi-species Coral Imagery}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {2723-2732} }
Learnable Prompt for Few-Shot Semantic Segmentation in Remote Sensing Domain-
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[arXiv]
[bibtex]@InProceedings{Immanuel_2024_CVPR, author = {Immanuel, Steve Andreas and Sinulingga, Hagai Raja}, title = {Learnable Prompt for Few-Shot Semantic Segmentation in Remote Sensing Domain}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {2755-2761} }
Zero-Shot Monocular Motion Segmentation in the Wild by Combining Deep Learning with Geometric Motion Model Fusion-
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[arXiv]
[bibtex]@InProceedings{Huang_2024_CVPR, author = {Huang, Yuxiang and Chen, Yuhao and Zelek, John}, title = {Zero-Shot Monocular Motion Segmentation in the Wild by Combining Deep Learning with Geometric Motion Model Fusion}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {2733-2743} }
Weakly-Supervised Temporal Action Localization with Multi-Modal Plateau Transformers-
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[supp]
[bibtex]@InProceedings{Hu_2024_CVPR, author = {Hu, Xin and Li, Kai and Patel, Deep and Kruus, Erik and Min, Martin Renqiang and Ding, Zhengming}, title = {Weakly-Supervised Temporal Action Localization with Multi-Modal Plateau Transformers}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {2704-2713} }
UVIS: Unsupervised Video Instance Segmentation-
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[supp]
[arXiv]
[bibtex]@InProceedings{Huang_2024_CVPR, author = {Huang, Shuaiyi and Suri, Saksham and Gupta, Kamal and Rambhatla, Sai Saketh and Lim, Ser-Nam and Shrivastava, Abhinav}, title = {UVIS: Unsupervised Video Instance Segmentation}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {2682-2692} }
Active Transferability Estimation-
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[bibtex]@InProceedings{Menta_2024_CVPR, author = {Menta, Tarun Ram and Jandial, Surgan and Patil, Akash and Bachu, Saketh and K.B, Vimal and Krishnamurthy, Balaji and Balasubramanian, Vineeth N. and Sarkar, Mausoom and Agarwal, Chirag}, title = {Active Transferability Estimation}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {2659-2670} }
SemiGPC: Distribution-Aware Label Refinement for Imbalanced Semi-Supervised Learning Using Gaussian Processes-
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[arXiv]
[bibtex]@InProceedings{Lemkhenter_2024_CVPR, author = {Lemkhenter, Abdelhak and Wang, Manchen and Zancato, Luca and Swaminathan, Gurumurthy and Favaro, Paolo and Modolo, Davide}, title = {SemiGPC: Distribution-Aware Label Refinement for Imbalanced Semi-Supervised Learning Using Gaussian Processes}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {2576-2585} }
Enrich Distill and Fuse: Generalized Few-Shot Semantic Segmentation in Remote Sensing Leveraging Foundation Model's Assistance-
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[bibtex]@InProceedings{Gao_2024_CVPR, author = {Gao, Tianyi and Ao, Wei and Wang, Xing-Ao and Zhao, Yuanhao and Ma, Ping and Xie, Mengjie and Fu, Hang and Ren, Jinchang and Gao, Zhi}, title = {Enrich Distill and Fuse: Generalized Few-Shot Semantic Segmentation in Remote Sensing Leveraging Foundation Model's Assistance}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {2771-2780} }
Dynamic Knowledge Adapter with Probabilistic Calibration for Generalized Few-Shot Semantic Segmentation-
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[bibtex]@InProceedings{Tong_2024_CVPR, author = {Tong, Jintao and Zhou, Haichen and Liu, Yicong and Hu, Yiman and Zou, Yixiong}, title = {Dynamic Knowledge Adapter with Probabilistic Calibration for Generalized Few-Shot Semantic Segmentation}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {2781-2790} }
Uncertainty-based Forgetting Mitigation for Generalized Few-Shot Object Detection-
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[bibtex]@InProceedings{Guirguis_2024_CVPR, author = {Guirguis, Karim and Eskandar, George and Wang, Mingyang and Kayser, Matthias and Monari, Eduardo and Yang, Bin and Beyerer, J\"urgen}, title = {Uncertainty-based Forgetting Mitigation for Generalized Few-Shot Object Detection}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {2586-2595} }
Image-caption Difficulty for Efficient Weakly-supervised Object Detection from In-the-wild Data-
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[bibtex]@InProceedings{Nebbia_2024_CVPR, author = {Nebbia, Giacomo and Kovashka, Adriana}, title = {Image-caption Difficulty for Efficient Weakly-supervised Object Detection from In-the-wild Data}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {2596-2605} }
MoDA: Leveraging Motion Priors from Videos for Advancing Unsupervised Domain Adaptation in Semantic Segmentation-
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[arXiv]
[bibtex]@InProceedings{Pan_2024_CVPR, author = {Pan, Fei and Yin, Xu and Lee, Seokju and Niu, Axi and Yoon, Sungeui and Kweon, In So}, title = {MoDA: Leveraging Motion Priors from Videos for Advancing Unsupervised Domain Adaptation in Semantic Segmentation}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {2649-2658} }
Generalized Few-Shot Meets Remote Sensing: Discovering Novel Classes in Land Cover Mapping via Hybrid Semantic Segmentation Framework-
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[arXiv]
[bibtex]@InProceedings{Li_2024_CVPR, author = {Li, Zhuohong and Lu, Fangxiao and Zou, Jiaqi and Hu, Lei and Zhang, Hongyan}, title = {Generalized Few-Shot Meets Remote Sensing: Discovering Novel Classes in Land Cover Mapping via Hybrid Semantic Segmentation Framework}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {2744-2754} }
CDAD-Net: Bridging Domain Gaps in Generalized Category Discovery-
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[bibtex]@InProceedings{Rongali_2024_CVPR, author = {Rongali, Sai Bhargav and Mehrotra, Sarthak and Jha, Ankit and C, Mohamad Hassan N and Bose, Shirsha and Gupta, Tanisha and Singha, Mainak and Banerjee, Biplab}, title = {CDAD-Net: Bridging Domain Gaps in Generalized Category Discovery}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {2616-2626} }
Latent-based Diffusion Model for Long-tailed Recognition-
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[arXiv]
[bibtex]@InProceedings{Han_2024_CVPR, author = {Han, Pengxiao and Ye, Changkun and Zhou, Jieming and Zhang, Jing and Hong, Jie and Li, Xuesong}, title = {Latent-based Diffusion Model for Long-tailed Recognition}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {2639-2648} }
On Accuracy and Speed of Geodesic Regression: Do Geometric Priors Improve Learning on Small Datasets?-
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[bibtex]@InProceedings{Myers_2024_CVPR, author = {Myers, Adele and Miolane, Nina}, title = {On Accuracy and Speed of Geodesic Regression: Do Geometric Priors Improve Learning on Small Datasets?}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {2714-2722} }
What is Point Supervision Worth in Video Instance Segmentation?-
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[arXiv]
[bibtex]@InProceedings{Huang_2024_CVPR, author = {Huang, Shuaiyi and Huang, De-An and Yu, Zhiding and Lan, Shiyi and Radhakrishnan, Subhashree and Alvarez, Jose M. and Shrivastava, Abhinav and Anandkumar, Anima}, title = {What is Point Supervision Worth in Video Instance Segmentation?}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {2671-2681} }
Audio-Visual Generalized Zero-Shot Learning using Pre-Trained Large Multi-Modal Models-
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[supp]
[bibtex]@InProceedings{Kurzendorfer_2024_CVPR, author = {Kurzend\"orfer, David and Mercea, Otniel-Bogdan and Koepke, A. Sophia and Akata, Zeynep}, title = {Audio-Visual Generalized Zero-Shot Learning using Pre-Trained Large Multi-Modal Models}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {2627-2638} }
Learning Tracking Representations from Single Point Annotations-
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[supp]
[arXiv]
[bibtex]@InProceedings{Wu_2024_CVPR, author = {Wu, Qiangqiang and Chan, Antoni B.}, title = {Learning Tracking Representations from Single Point Annotations}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2024}, pages = {2606-2615} }