Interactive Labeling and Data Augmentation for Vision
Data Augmentation for Scene Text Recognition-
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[arXiv]
[bibtex]@InProceedings{Atienza_2021_ICCV, author = {Atienza, Rowel}, title = {Data Augmentation for Scene Text Recognition}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops}, month = {October}, year = {2021}, pages = {1561-1570} }
Nuisance-Label Supervision: Robustness Improvement by Free Labels-
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[supp]
[arXiv]
[bibtex]@InProceedings{Wei_2021_ICCV, author = {Wei, Xinyue and Qiu, Weichao and Zhang, Yi and Xiao, Zihao and Yuille, Alan}, title = {Nuisance-Label Supervision: Robustness Improvement by Free Labels}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops}, month = {October}, year = {2021}, pages = {1541-1550} }
Interactive Labeling for Human Pose Estimation in Surveillance Videos-
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[supp]
[bibtex]@InProceedings{Cormier_2021_ICCV, author = {Cormier, Mickael and R\"opke, Fabian and Golda, Thomas and Beyerer, J\"urgen}, title = {Interactive Labeling for Human Pose Estimation in Surveillance Videos}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops}, month = {October}, year = {2021}, pages = {1649-1658} }
Using Synthetic Data Generation To Probe Multi-View Stereo Networks-
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[supp]
[bibtex]@InProceedings{Acharya_2021_ICCV, author = {Acharya, Pranav and Lohn, Daniel and Ross, Vivian and Ha, Maya and Rich, Alexander and Sayyad, Ehsan and H\"ollerer, Tobias}, title = {Using Synthetic Data Generation To Probe Multi-View Stereo Networks}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops}, month = {October}, year = {2021}, pages = {1583-1591} }
Bounding Box Dataset Augmentation for Long-Range Object Distance Estimation-
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[bibtex]@InProceedings{Franke_2021_ICCV, author = {Franke, Marten and Gopinath, Vaishnavi and Reddy, Chaitra and Risti\'c-Durrant, Danijela and Michels, Kai}, title = {Bounding Box Dataset Augmentation for Long-Range Object Distance Estimation}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops}, month = {October}, year = {2021}, pages = {1669-1677} }
Weakly-Supervised Semantic Segmentation by Learning Label Uncertainty-
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[arXiv]
[bibtex]@InProceedings{Neven_2021_ICCV, author = {Neven, Robby and Neven, Davy and De Brabandere, Bert and Proesmans, Marc and Goedem\'e, Toon}, title = {Weakly-Supervised Semantic Segmentation by Learning Label Uncertainty}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops}, month = {October}, year = {2021}, pages = {1678-1686} }
Reducing Label Effort: Self-Supervised Meets Active Learning-
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[arXiv]
[bibtex]@InProceedings{Bengar_2021_ICCV, author = {Bengar, Javad Zolfaghari and van de Weijer, Joost and Twardowski, Bartlomiej and Raducanu, Bogdan}, title = {Reducing Label Effort: Self-Supervised Meets Active Learning}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops}, month = {October}, year = {2021}, pages = {1631-1639} }
Multi-Domain Conditional Image Translation: Translating Driving Datasets From Clear-Weather to Adverse Conditions-
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[supp]
[bibtex]@InProceedings{Vinod_2021_ICCV, author = {Vinod, Vishal and Prabhakar, K. Ram and Babu, R. Venkatesh and Chakraborty, Anirban}, title = {Multi-Domain Conditional Image Translation: Translating Driving Datasets From Clear-Weather to Adverse Conditions}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops}, month = {October}, year = {2021}, pages = {1571-1582} }
EdgeFlow: Achieving Practical Interactive Segmentation With Edge-Guided Flow-
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[arXiv]
[bibtex]@InProceedings{Hao_2021_ICCV, author = {Hao, Yuying and Liu, Yi and Wu, Zewu and Han, Lin and Chen, Yizhou and Chen, Guowei and Chu, Lutao and Tang, Shiyu and Yu, Zhiliang and Chen, Zeyu and Lai, Baohua}, title = {EdgeFlow: Achieving Practical Interactive Segmentation With Edge-Guided Flow}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops}, month = {October}, year = {2021}, pages = {1551-1560} }
Learning to Localise and Count With Incomplete Dot-Annotations-
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[bibtex]@InProceedings{Chen_2021_ICCV, author = {Chen, Feng and Pound, Michael P. and French, Andrew P.}, title = {Learning to Localise and Count With Incomplete Dot-Annotations}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops}, month = {October}, year = {2021}, pages = {1612-1620} }
Class-Agnostic Segmentation Loss and Its Application to Salient Object Detection and Segmentation-
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[supp]
[arXiv]
[bibtex]@InProceedings{Sharma_2021_ICCV, author = {Sharma, Angira and Khan, Naeemullah and Mubashar, Muhammad and Sundaramoorthi, Ganesh and Torr, Philip}, title = {Class-Agnostic Segmentation Loss and Its Application to Salient Object Detection and Segmentation}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops}, month = {October}, year = {2021}, pages = {1621-1630} }
All You Need Are a Few Pixels: Semantic Segmentation With PixelPick-
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[supp]
[arXiv]
[bibtex]@InProceedings{Shin_2021_ICCV, author = {Shin, Gyungin and Xie, Weidi and Albanie, Samuel}, title = {All You Need Are a Few Pixels: Semantic Segmentation With PixelPick}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops}, month = {October}, year = {2021}, pages = {1687-1697} }
Object-Based Augmentation for Building Semantic Segmentation: Ventura and Santa Rosa Case Study-
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[bibtex]@InProceedings{Illarionova_2021_ICCV, author = {Illarionova, Svetlana and Nesteruk, Sergey and Shadrin, Dmitrii and Ignatiev, Vladimir and Pukalchik, Mariia and Oseledets, Ivan}, title = {Object-Based Augmentation for Building Semantic Segmentation: Ventura and Santa Rosa Case Study}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops}, month = {October}, year = {2021}, pages = {1659-1668} }
Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark-
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[arXiv]
[bibtex]@InProceedings{Qiu_2021_ICCV, author = {Qiu, Shuhao and Zhu, Chuang and Zhou, Wenli}, title = {Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops}, month = {October}, year = {2021}, pages = {1592-1601} }
InAugment: Improving Classifiers via Internal Augmentation-
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[supp]
[arXiv]
[bibtex]@InProceedings{Arar_2021_ICCV, author = {Arar, Moab and Shamir, Ariel and Bermano, Amit}, title = {InAugment: Improving Classifiers via Internal Augmentation}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops}, month = {October}, year = {2021}, pages = {1698-1707} }
Self-Improving Classification Performance Through GAN Distillation-
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[bibtex]@InProceedings{Pennisi_2021_ICCV, author = {Pennisi, Matteo and Palazzo, Simone and Spampinato, Concetto}, title = {Self-Improving Classification Performance Through GAN Distillation}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops}, month = {October}, year = {2021}, pages = {1640-1648} }
Localizing Human Keypoints Beyond the Bounding Box-
[pdf]
[bibtex]@InProceedings{Park_2021_ICCV, author = {Park, Soonchan and Park, Jinah}, title = {Localizing Human Keypoints Beyond the Bounding Box}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops}, month = {October}, year = {2021}, pages = {1602-1611} }