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Today, state-of-the-art deep neural networks that process event-camera data first convert a temporal window of events into dense, grid-like input representations.
Prefix sums and their applications
Guy E. Blelloch · 1990
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
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Ssd: Single shot multibox detector
Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, and Alexander C. Berg · 2016
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You only look once: Unified, real-time object detection
Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi · 2016
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Pseudo-labels for supervised learning on dynamic vision sensor data, applied to object detection under ego-motion
Nicholas F. Y. Chen · 2018
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Towards event-driven object detection with off-the-shelf deep learning
Massimiliano Iacono, Stefan Weber, Arren Glover, and Chiara Bartolozzi · 2018
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Yolov3: An incremental improvement
Joseph Redmon and Ali Farhadi · 2018
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Super-convergence: Very fast training of residual networks using large learning rates
Leslie N. Smith and Nicholay Topin · 2018
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Asynchronous convolutional networks for object detection in neuromorphic cameras
Marco Cannici, Marco Ciccone, Andrea Romanoni, and Matteo Matteucci · 2019
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Mixed frame-/event-driven fast pedestrian detection
Zhuangyi Jiang, Pengfei Xia, Kai Huang, Walter Stechele, Guang Chen, Zhenshan Bing, and Alois Knoll · 2019
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A large scale event-based detection dataset for automotive
Pierre de Tournemire, Davide Nitti, Etienne Perot, Davide Migliore, and Amos Sironi · 2020
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Dynamic obstacle avoidance for quadrotors with event cameras
Davide Falanga, Kevin Kleber, and Davide Scaramuzza · 2020
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Event-based vision: A survey
Guillermo Gallego, Tobi Delbrück, Garrick Orchard, Chiara Bartolozzi, Brian Taba, Andrea Censi, Stefan Leutenegger, Andrew J. Davison, Jörg Conradt, Kostas Daniilidis, and Davide Scaramuzza · 2020
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Hippo: Recurrent memory with optimal polynomial projections
Albert Gu, Tri Dao, Stefano Ermon, Atri Rudra, and Christopher Ré · 2020
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Event-based asynchronous sparse convolutional networks
Nico Messikommer, Daniel Gehrig, Antonio Loquercio, and Davide Scaramuzza · 2020
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Learning to detect objects with a 1 megapixel event camera
Etienne Perot, Pierre de Tournemire, Davide Nitti, Jonathan Masci, and Amos Sironi · 2020
Cited alongside, same era.
Learning from event cameras with sparse spiking convolutional neural networks
Loic Cordone, Benoît Miramond, and Sonia Ferrante · 2021
Cited alongside, same era.
Yolox: Exceeding yolo series in 2021
Zheng Ge, Songtao Liu, Feng Wang, Zeming Li, and Jian Sun · 2021
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DSEC: A stereo event camera dataset for driving scenarios
Mathias Gehrig, Willem Aarents, Daniel Gehrig, and Davide Scaramuzza · 2021
Cited alongside, same era.
Aegnn: Asynchronous event-based graph neural networks
Simon Schaefer, Daniel Gehrig, and Davide Scaramuzza · 2022
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Nested hierarchical transformer: Towards accurate, data-efficient and interpretable visual understanding
Zizhao Zhang, Han Zhang, Long Zhao, Ting Chen, , Sercan Ö. Arık, and Tomas Pfister · 2022
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Optical flow estimation from event-based cameras and spiking neural networks
Javier Cuadrado, Ulysse Rançon, Benoit R. Cottereau, Francisco Barranco, and Timothée Masquelier · 2023
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Recurrent vision transformers for object detection with event cameras
Mathias Gehrig and Davide Scaramuzza · 2023
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How to train your hippo: State space models with generalized basis projections
Albert Gu, Isys Johnson, Aman Timalsina, Atri Rudra, and Christopher Ré · 2023
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Albert Gu, Isys Johnson, Karan Goel, Khaled Saab, Tri Dao, Atri Rudra, and Christopher Ré · 2021
Cited alongside, same era.
Time lens: Event-based video frame interpolation
Stepan Tulyakov, Daniel Gehrig, Stamatios Georgoulis, Julius Erbach, Mathias Gehrig, Yuanyou Li, and Davide Scaramuzza · 2021
Cited alongside, same era.
An effective loss function for generating 3d models from single 2d image without rendering
Nikola Zubić and Pietro Liò · 2021
Cited alongside, same era.
Adversarial attacks on spiking convolutional neural networks for event-based vision
Julian Büchel, Gregor Lenz, Yalun Hu, Sadique Sheik, and Martino Sorbaro · 2022
Cited alongside, same era.
Object detection with spiking neural networks on automotive event data
Loic Cordone, Benoît Miramond, and Phillipe Thierion · 2022
Cited alongside, same era.
Pushing the limits of asynchronous graph-based object detection with event cameras, 2022
Daniel Gehrig and Davide Scaramuzza · 2022
Cited alongside, same era.
It’s raw! audio generation with state-space models
Karan Goel, Albert Gu, Chris Donahue, and Christopher Ré · 2022
Cited alongside, same era.
Memory-efficient graph convolutional networks for object classification and detection with event cameras
Kamil Jeziorek, Andrea Pinna, and Tomasz Kryjak · 2023
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Sodformer: Streaming object detection with transformer using events and frames
Dianze Li, Yonghong Tian, and Jianing Li · 2023
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Get: Group event transformer for event-based vision
Yansong Peng, Yueyi Zhang, Zhiwei Xiong, Xiaoyan Sun, and Feng Wu · 2023
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Dynamic vision-based satellite detection: A time-based encoding approach with spiking neural networks
Nikolaus Salvatore and Justin Fletcher · 2023
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Simplified state space layers for sequence modeling
Jimmy T.H. Smith, Andrew Warrington, and Scott Linderman · 2023
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Event-based object detection using graph neural networks
Daobo Sun and Haibo Ji · 2023
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Eventclip: Adapting clip for event-based object recognition
Ziyi Wu, Xudong Liu, and Igor Gilitschenski · 2023
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From chaos comes order: Ordering event representations for object recognition and detection
Nikola Zubić, Daniel Gehrig, Mathias Gehrig, and Davide Scaramuzza · 2023
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