One-shot imitation learning, 2017. ,
Matching networks for one shot learning, Advances in neural information processing systems, pp.3630-3638, 2016. ,
Learning to remember rare events, 2017. ,
Low data drug discovery with one-shot learning, ACS central science, vol.3, issue.4, pp.283-293, 2017. ,
One-shot learning of object categories, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.28, issue.4, pp.594-611, 2006. ,
Model-agnostic meta-learning for fast adaptation of deep networks, Proceedings of the 34th International Conference on Machine Learning, vol.70, pp.1126-1135, 2017. ,
Optimization as a model for few-shot learning, International Conference on Learning Representations (ICLR, 2017. ,
Fully convolutional networks for semantic segmentation, Proceedings of the IEEE conference on computer vision and pattern recognition, pp.3431-3440, 2015. ,
Segnet: A deep convolutional encoder-decoder architecture for image segmentation, IEEE Transactions on Pattern Analysis & Machine Intelligence, issue.12, pp.2481-2495, 2017. ,
U-net: Convolutional networks for biomedical image segmentation, International Conference on Medical image computing and computer-assisted intervention, pp.234-241, 2015. ,
Refinenet: Multi-path refinement networks for high-resolution semantic segmentation, CoRR, 2016. ,
Semantic image segmentation with deep convolutional nets and fully connected crfs, 2014. ,
Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs, CoRR, 2016. ,
Encoder-decoder with atrous separable convolution for semantic image segmentation, 2018. ,
Attention to scale: Scale-aware semantic image segmentation, Proceedings of the IEEE conference on computer vision and pattern recognition, pp.3640-3649, 2016. ,
End-to-end instance segmentation and counting with recurrent attention, CoRR, 2016. ,
Attention-guided unified network for panoptic segmentation, CoRR, 2018. ,
Attention is all you need, CoRR, 2017. ,
Squeeze-and-excitation networks, CoRR, 2017. ,
Revisiting metric learning for few-shot image classification, ArXiv, 2019. ,
Few-shot learning with graph neural networks, 2017. ,
Prototypical networks for few-shot learning, Advances in neural information processing systems, pp.4077-4087, 2017. ,
Oneshot learning for semantic segmentation, 2017. ,
Conditional networks for few-shot semantic segmentation, 2018. ,
Few-shot semantic segmentation with prototype learning, BMVC, vol.3, 2018. ,
Multiscale discriminative location-aware network for fewshot semantic segmentation, 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC), vol.2, pp.42-47, 2019. ,
Adaptive masked proxies for few-shot segmentation, 2019. ,
Attention-based multi-context guiding for fewshot semantic segmentation, Proceedings of the AAAI Conference on Artificial Intelligence, vol.33, pp.8441-8448, 2019. ,
Sg-one: Similarity guidance network for one-shot semantic segmentation, 2018. ,
Panet: Few-shot image semantic segmentation with prototype alignment, Proceedings of the IEEE International Conference on Computer Vision, pp.9197-9206, 2019. ,
Very deep convolutional networks for large-scale image recognition, 2014. ,
Network in network, 2013. ,
URL : https://hal.archives-ouvertes.fr/hal-01551350
The PASCAL Visual Object Classes Challenge 2012 (VOC2012) Results ,
Semantic contours from inverse detectors, 2011 International Conference on Computer Vision, pp.991-998, 2011. ,
Pytorch: An imperative style, high-performance deep learning library, Advances in Neural Information Processing Systems, pp.8024-8035, 2019. ,
Imagenet large scale visual recognition challenge, International journal of computer vision, vol.115, issue.3, pp.211-252, 2015. ,
Scribblesup: Scribble-supervised convolutional networks for semantic segmentation, CoRR, 2016. ,