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Algorithms that fuse multiple input sources benefit from both complementary and shared information.
Are we ready for autonomous driving? the kitti vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
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Deep neural networks for acoustic modeling in speech recognition
Geoffrey Hinton, Li Deng, Dong Yu, George Dahl, Abdel-rahman Mohamed, Navdeep Jaitly, Andrew Senior, Vincent Vanhoucke, Patrick Nguyen, Brian Kingsbury, et al · 2012
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Speech recognition with deep recurrent neural networks
Alex Graves, Abdel-rahman Mohamed, and Geoffrey Hinton · 2013
Earlier work this paper cites.
Audio-visual deep learning for noise robust speech recognition
Jing Huang and Brian Kingsbury · 2013
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Deep convolutional neural networks for lvcsr
Tara N Sainath, Abdel-rahman Mohamed, Brian Kingsbury, and Bhuvana Ramabhadran · 2013
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Online multimodal deep similarity learning with application to image retrieval
Pengcheng Wu, Steven CH Hoi, Hao Xia, Peilin Zhao, Dayong Wang, and Chunyan Miao · 2013
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Rich feature hierarchies for accurate object detection and semantic segmentation
Ross Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik · 2014
Earlier work this paper cites.
Stacked multiscale feature learning for domain independent medical image segmentation
Ryan Kiros, Karteek Popuri, Dana Cobzas, and Martin Jagersand · 2014
Earlier work this paper cites.
Attention-based models for speech recognition
Jan K Chorowski, Dzmitry Bahdanau, Dmitriy Serdyuk, Kyunghyun Cho, and Yoshua Bengio · 2015
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Fast r-cnn
Ross Girshick · 2015
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Explaining and harnessing adversarial examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy · 2015
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Deep learning
Yann LeCun, Yoshua Bengio, and Geoffrey Hinton · 2015
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Multimodal neuroimaging feature learning for multiclass diagnosis of alzheimer’s disease
Siqi Liu, Sidong Liu, Weidong Cai, Hangyu Che, Sonia Pujol, Ron Kikinis, Dagan Feng, Michael J Fulham, et al · 2015
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Deep multimodal learning for audio-visual speech recognition
Youssef Mroueh, Etienne Marcheret, and Vaibhava Goel · 2015
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Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
Cited alongside, same era.
Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2015
Cited alongside, same era.
Listening with your eyes: Towards a practical visual speech recognition system using deep boltzmann machines
Chao Sui, Mohammed Bennamoun, and Roberto Togneri · 2015
Cited alongside, same era.
Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
Cited alongside, same era.
Pose-rcnn: Joint object detection and pose estimation using 3d object proposals
Markus Braun, Qing Rao, Yikang Wang, and Fabian Flohr · 2016
Cited alongside, same era.
Car detection for autonomous vehicle: Lidar and vision fusion approach through deep learning framework
Xinxin Du, Marcelo H Ang, and Daniela Rus · 2017
Later among the works it cites.
Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
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Densely connected convolutional networks
Gao Huang, Zhuang Liu, Laurens Van Der Maaten, and Kilian Q Weinberger · 2017
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Deep multimodal learning: A survey on recent advances and trends
Dhanesh Ramachandram and Graham W Taylor · 2017
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Yolo9000: better, faster, stronger
Joseph Redmon and Ali Farhadi · 2017
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Adapnet: Adaptive semantic segmentation in adverse environmental conditions
Abhinav Valada, Johan Vertens, Ankit Dhall, and Wolfram Burgard · 2017
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William Chan, Navdeep Jaitly, Quoc Le, and Oriol Vinyals · 2016
Cited alongside, same era.
R-fcn: Object detection via region-based fully convolutional networks
Jifeng Dai, Yi Li, Kaiming He, and Jian Sun · 2016
Cited alongside, same era.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Cited alongside, same era.
Robust detection of non-motorized road users using deep learning on optical and lidar data
Taewan Kim and Joydeep Ghosh · 2016
Cited alongside, same era.
Ssd: Single shot multibox detector
Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, and Alexander C Berg · 2016
Cited alongside, same era.
Choosing smartly: Adaptive multimodal fusion for object detection in changing environments
Oier Mees, Andreas Eitel, and Wolfram Burgard · 2016
Cited alongside, same era.
You only look once: Unified, real-time object detection
Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi · 2016
Cited alongside, same era.
State-of-the-art speech recognition with sequence-to-sequence models
Chung-Cheng Chiu, Tara N Sainath, Yonghui Wu, Rohit Prabhavalkar, Patrick Nguyen, Zhifeng Chen, Anjuli Kannan, Ron J Weiss, Kanishka Rao, Ekaterina Gonina, et al · 2018
Later among the works it cites.
Joint 3d proposal generation and object detection from view aggregation
Jason Ku, Melissa Mozifian, Jungwook Lee, Ali Harakeh, and Steven L Waslander · 2018
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Deep continuous fusion for multi-sensor 3d object detection
Ming Liang, Bin Yang, Shenlong Wang, and Raquel Urtasun · 2018
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Frustum pointnets for 3d object detection from rgb-d data
Charles R Qi, Wei Liu, Chenxia Wu, Hao Su, and Leonidas J Guibas · 2018
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Fusing bird’s eye view lidar point cloud and front view camera image for 3d object detection
Zining Wang, Wei Zhan, and Masayoshi Tomizuka · 2018
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Di Feng, Christian Haase-Schuetz, Lars Rosenbaum, Heinz Hertlein, Fabian Duffhauss, Claudius Glaeser, Werner Wiesbeck, and Klaus Dietmayer · 2019
Closest in time.
Multi-task multi-sensor fusion for 3d object detection
Ming Liang, Bin Yang, Yun Chen, Rui Hui, and Raquel Urtasun · 2019
Closest in time.
Robustness may be at odds with accuracy
Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Alexander Turner, and Aleksander Madry · 2019
Closest in time.