Hierarchical attentive recurrent tracking
Class-agnostic object tracking is particularly difficult in cluttered environments as target specific discriminative models cannot be learned a priori. Inspired by how the human visual cortex employs spatial attention and separate “where” and “what” processing pathways to actively suppress irrelevan...
Asıl Yazarlar: | Kosiorek, A, Bewley, A, Posner, H |
---|---|
Materyal Türü: | Conference item |
Baskı/Yayın Bilgisi: |
Neural Information Processing Systems
2018
|
Benzer Materyaller
-
Deep tracking in the wild: End-to-end tracking using recurrent neural networks
Yazar:: Dequaire, J, ve diğerleri
Baskı/Yayın Bilgisi: (2017) -
Attentional control, rumination and recurrence of depression
Yazar:: Figueroa, C, ve diğerleri
Baskı/Yayın Bilgisi: (2019) -
End-to-end tracking and semantic segmentation using recurrent neural networks
Yazar:: Ondruska, P, ve diğerleri
Baskı/Yayın Bilgisi: (2016) -
Neural stethoscopes: Unifying analytic, auxiliary and adversarial network probing
Yazar:: Fuchs, F, ve diğerleri
Baskı/Yayın Bilgisi: (2018) -
Hierarchical feature attention with bottleneck attention modules for multi-branch classification
Yazar:: Gan, Ryan
Baskı/Yayın Bilgisi: (2024)