Self-supervisory Signals for Object Discovery and Detection

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Facenet: A unified embedding for face recognition and clustering

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Faster r-cnn: Towards real-time object detection with region proposal networks

Ren, S., He, K., Girshick, R., Sun, J.: · 2015

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Unsupervised object discovery and tracking in video collections

Kwak, S., Cho, M., Laptev, I., Ponce, J., Schmid, C.: · 2015

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Learning to see by moving

Agrawal, P., Carreira, J., Malik, J.: · 2015

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Unsupervised learning of visual representations using videos

Original

Wang, X., Gupta, A.: · 2015

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The moped framework: Object recognition and pose estimation for manipulation

Collet, A., Martinez, M., , Srinivasa, S.: · 2016

Deep residual learning for image recognition

He, K., Zhang, X., Ren, S., Sun, J.: · 2016

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Learning features by watching objects move

Pathak, D., Girshick, R., Dollár, P., Darrell, T., Hariharan, B.: · 2017

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Curiosity-driven exploration by self-supervised prediction

Pathak, D., Agrawal, P., Efros, A.A., Darrell, T.: · 2017

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A self-supervised learning system for object detection using physics simulation and multi-view pose estimation

Mitash, C., Bekris, K.E., Boularias, A.: · 2017

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Time-contrastive networks: Self-supervised learning from multi-view observation

Original

Sermanet, P., Lynch, C., Hsu, J., Levine, S.: · 2017

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A dataset for developing and benchmarking active vision