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Event-based attention and tracking on neuromorphic hardware

arXiv 1907.04060 ↗First posted 9 Jul 2019cs.NE eess.IVcited by 14

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Abstract (arXiv)

We present a fully event-driven vision and processing system for selective attention and tracking, realized on a neuromorphic processor Loihi interfaced to an event-based Dynamic Vision Sensor DAVIS. The attention mechanism is realized as a recurrent spiking neural network that implements attractor-dynamics of dynamic neural fields. We demonstrate capability of the system to create sustained activation that supports object tracking when distractors are present or when the object slows down or stops, reducing the number of generated events.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Jul 2019.

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Citing papers per year: 2021: 3; 2022: 2; 2023: 2; 2024: 5; 2025: 2.

14 papers.

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  1. 2021SpikeMS: Deep Spiking Neural Network for Motion Segmentationcited by 29
  2. 2023Neuromorphic Event-based Facial Expression Recognitioncited by 18
  3. 2022How Many Events do You Need? Event-based Visual Place Recognition Using Sparse But Varying Pixelscited by 17
  4. 2024Fully Spiking Actor Network with Intra-layer Connections for Reinforcement Learningcited by 10
  5. 2021SpikE: spike-based embeddings for multi-relational graph datacited by 9
  6. 2025AceVFI: A Comprehensive Survey of Advances in Video Frame Interpolationcited by 8
  7. 2024Neuromorphic Facial Analysis with Cross-Modal Supervisioncited by 7
  8. 2022Visual Odometry with Neuromorphic Resonator Networkscited by 5
  9. 2024Neuromorphic Valence and Arousal Estimationcited by 5
  10. 2023NeuroCLIP: Neuromorphic Data Understanding by CLIP and SNNcited by 4
  11. 2024Spatio-temporal Transformers for Action Unit Classification with Event Camerascited by 2
  12. 2021Bio-inspired visual attention for silicon retinas based on spiking neural networks applied to pattern classificationcited by 1
2 more
  1. 2024Maelstrom Networkscited by 0
  2. 2025Event-driven Robust Fitting on Neuromorphic Hardwarecited by 0