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Few-shot instance segmentation extends the few-shot learning paradigm to the instance segmentation task, which tries to segment instance objects from a query image with a few annotated examples of novel categories.
The Pascal Visual Object Classes (VOC) Challenge
Everingham, M.; Gool, L. V.; Williams, C. K. I.; Winn, J. M.; and Zisserman, A. 2010 · 2010
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Generative Adversarial Nets
Goodfellow, I.; Pouget-Abadie, J.; Mirza, M.; Xu, B.; Warde-Farley, D.; Ozair, S.; Courville, A.; and Bengio, Y. 2014 · 2014
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Microsoft COCO: Common Objects in Context
Lin, T.-Y.; Maire, M.; Belongie, S. J.; Hays, J.; Perona, P.; Ramanan, D.; Dollár, P.; and Zitnick, C. L. 2014 · 2014
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Fully convolutional networks for semantic segmentation
Long, J.; Shelhamer, E.; and Darrell, T. 2015 · 2015
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Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Ren, S.; He, K.; Girshick, R.; and Sun, J. 2015 · 2015
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U-Net: Convolutional Networks for Biomedical Image Segmentation
Ronneberger, O.; Fischer, P.; and Brox, T. 2015 · 2015
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Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Sohl-Dickstein, J.; Weiss, E.; Maheswaranathan, N.; and Ganguli, S. 2015 · 2015
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Fully convolutional networks for semantic segmentation
Long, J.; Shelhamer, E.; and Darrell, T. 2015 · 2015
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Deep Residual Learning for Image Recognition
He, K.; Zhang, X.; Ren, S.; and Sun, J. 2016 · 2016
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Mask R-CNN
He, K.; Gkioxari, G.; Dollar, P.; and Girshick, R. 2017 · 2017
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Feature Pyramid Networks for Object Detection
Lin, T.-Y.; Dollar, P.; Girshick, R.; He, K.; Hariharan, B.; and Belongie, S. 2017 · 2017
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Attention is All you Need
Vaswani, A.; Shazeer, N.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A. N.; Kaiser, L. u.; and Polosukhin, I. 2017 · 2017
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Mask R-CNN
He, K.; Gkioxari, G.; Dollar, P.; and Girshick, R. 2017 · 2017
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One-Shot Instance Segmentation
Michaelis, C.; Ustyuzhaninov, I.; Bethge, M.; and Ecker, A. S. 2018 · 2018
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Few-Shot Object Detection via Feature Reweighting
Kang, B.; Liu, Z.; Wang, X.; Yu, F.; Feng, J.; and Darrell, T. 2019 · 2019
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Generative Modeling by Estimating Gradients of the Data Distribution
Song, Y.; and Ermon, S. 2019 · 2019
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Meta r-cnn: Towards general solver for instance-level low-shot learning
Yan, X.; Chen, Z.; Xu, A.; Wang, X.; Liang, X.; and Lin, L. 2019 · 2019
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Generative Modeling by Estimating Gradients of the Data Distribution
Song, Y.; and Ermon, S. 2019 · 2019
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Meta r-cnn: Towards general solver for instance-level low-shot learning
Yan, X.; Chen, Z.; Xu, A.; Wang, X.; Liang, X.; and Lin, L. 2019 · 2019
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FGN: Fully Guided Network for Few-Shot Instance Segmentation
Fan, Z.; Yu, J.-G.; Liang, Z.; Ou, J.; Gao, C.; Xia, G.-S.; and Li, Y. 2020 · 2020
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Denoising Diffusion Probabilistic Models
Ho, J.; Jain, A.; and Abbeel, P. 2020 · 2020
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Frustratingly Simple Few-Shot Object Detection
Wang, X.; Huang, T.; Gonzalez, J.; Darrell, T.; and Yu, F. 2020 · 2020
Classifier-Free Diffusion Guidance
Ho, J.; and Salimans, T. 2021 · 2021
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Class-incremental few-shot object detection
Li, P.; Li, Y.; Cui, H.; and Wang, D. 2021 · 2021
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FAPIS: A Few-Shot Anchor-Free Part-Based Instance Segmenter
Nguyen, K.; and Todorovic, S. 2021 · 2021
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Label-Efficient Semantic Segmentation with Diffusion Models
Baranchuk, D.; Voynov, A.; Rubachev, I.; Khrulkov, V.; and Babenko, A. 2022 · 2022
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Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems Through Stochastic Contraction
Chung, H.; Sim, B.; and Ye, J. C. 2022 · 2022
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Vector Quantized Diffusion Model for Text-to-Image Synthesis
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Denoising Diffusion Probabilistic Models
Ho, J.; Jain, A.; and Abbeel, P. 2020 · 2020
Cited alongside, same era.
Incremental few-shot object detection
Perez-Rua, J.-M.; Zhu, X.; Hospedales, T. M.; and Xiang, T. 2020 · 2020
Cited alongside, same era.
Frustratingly Simple Few-Shot Object Detection
Wang, X.; Huang, T.; Gonzalez, J.; Darrell, T.; and Yu, F. 2020 · 2020
Cited alongside, same era.
Few-shot object detection and viewpoint estimation for objects in the wild
Xiao, Y.; and Marlet, R. 2020 · 2020
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Diffusion Models Beat GANs on Image Synthesis
Dhariwal, P.; and Nichol, A. 2021 · 2021
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Incremental Few-Shot Instance Segmentation
Ganea, D. A.; Boom, B.; Poppe, R.; and Abc, X. 2021 · 2021
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Gu, S.; Chen, D.; Bao, J.; Wen, F.; Zhang, B.; Chen, D.; Yuan, L.; and Guo, B. 2022 · 2022
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Cascaded Diffusion Models for High Fidelity Image Generation
Ho, J.; Saharia, C.; Chan, W.; Fleet, D. J.; Norouzi, M.; and Salimans, T. 2022 · 2022
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DiffusionCLIP: Text-Guided Diffusion Models for Robust Image Manipulation
Kim, G.; Kwon, T.; and Ye, J. C. 2022 · 2022
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Camouflaged Instance Segmentation In-The-Wild: Dataset, Method, and Benchmark Suite
Le, T.-N.; Cao, Y.; Nguyen, T.-C.; Le, M.-Q.; Nguyen, K.-D.; Do, T.-T.; Tran, M.-T.; and Nguyen, T. V. 2022 · 2022
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RePaint: Inpainting Using Denoising Diffusion Probabilistic Models
Lugmayr, A.; Danelljan, M.; Romero, A.; Yu, F.; Timofte, R.; and Van Gool, L. 2022 · 2022
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iFS-RCNN: An Incremental Few-Shot Instance Segmenter
Nguyen, K.; Todorovic, S.; Abc, X.; and Abc, X. 2022 · 2022
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High-Resolution Image Synthesis With Latent Diffusion Models
Rombach, R.; Blattmann, A.; Lorenz, D.; Esser, P.; and Ommer, B. 2022 · 2022
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Dynamic Transformer for Few-Shot Instance Segmentation
Wang, H.; Liu, J.; Liu, Y.; Maji, S.; Sonke, J.-J.; and Gavves, E. 2022 · 2022
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iFS-RCNN: An Incremental Few-Shot Instance Segmenter
Nguyen, K.; Todorovic, S.; Abc, X.; and Abc, X. 2022 · 2022
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Dynamic Transformer for Few-Shot Instance Segmentation
Wang, H.; Liu, J.; Liu, Y.; Maji, S.; Sonke, J.-J.; and Gavves, E. 2022 · 2022
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