{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,8]],"date-time":"2024-09-08T14:26:05Z","timestamp":1725805565892},"reference-count":53,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,5,30]],"date-time":"2021-05-30T00:00:00Z","timestamp":1622332800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,5,30]],"date-time":"2021-05-30T00:00:00Z","timestamp":1622332800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,5,30]],"date-time":"2021-05-30T00:00:00Z","timestamp":1622332800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,5,30]]},"DOI":"10.1109\/icra48506.2021.9561904","type":"proceedings-article","created":{"date-parts":[[2021,10,19]],"date-time":"2021-10-19T20:28:35Z","timestamp":1634675315000},"page":"4875-4881","source":"Crossref","is-referenced-by-count":18,"title":["Perceive, Attend, and Drive: Learning Spatial Attention for Safe Self-Driving"],"prefix":"10.1109","author":[{"given":"Bob","family":"Wei","sequence":"first","affiliation":[]},{"given":"Mengye","family":"Ren","sequence":"additional","affiliation":[]},{"given":"Wenyuan","family":"Zeng","sequence":"additional","affiliation":[]},{"given":"Ming","family":"Liang","sequence":"additional","affiliation":[]},{"given":"Bin","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Raquel","family":"Urtasun","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","article-title":"Baidu apollo EM motion planner","author":"fan","year":"2018","journal-title":"CoRR"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00886"},{"key":"ref33","article-title":"On a formal model of safe and scalable self-driving cars","author":"shalev-shwartz","year":"2017","journal-title":"CoRR"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00197"},{"key":"ref31","article-title":"Learning to reweight examples for robust deep learning","author":"ren","year":"2018","journal-title":"ICML"},{"key":"ref30","article-title":"Adaptive auxiliary task weighting for reinforcement learning","author":"lin","year":"2019","journal-title":"NeurIPS"},{"key":"ref37","article-title":"Testing the safety of self-driving vehicles by simulating perception and prediction","author":"wong","year":"2020","journal-title":"ECCV"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2018.8569425"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2018.8569332"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2018.8569580"},{"key":"ref28","article-title":"GradNorm: Gradient normalization for adaptive loss balancing in deep multitask networks","author":"chen","year":"2018","journal-title":"ICML"},{"key":"ref27","article-title":"Multi-task learning using uncertainty to weigh losses for scene geometry and semantics","author":"kendall","year":"2018","journal-title":"CVPR"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01270-0_17"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.194"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.683"},{"key":"ref20","article-title":"Speeding up convolutional neural networks by exploiting the sparsity of rectifier units","author":"shi","year":"2017","journal-title":"CoRR"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00961"},{"key":"ref21","article-title":"Perforatedcnns: Acceleration through elimination of redundant convolutions","author":"figurnov","year":"2016","journal-title":"NIPS"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2019.00114"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.684"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.298"},{"key":"ref25","article-title":"Sparse convolutional neural networks","author":"liu","year":"2015","journal-title":"CVPR"},{"key":"ref50","article-title":"Estimating or propagating gradients through stochastic neurons for conditional computation","author":"bengio","year":"2013","journal-title":"CoRR"},{"key":"ref51","article-title":"nuscenes: A multimodal dataset for autonomous driving","author":"caesar","year":"2019","journal-title":"CoRR"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.660"},{"key":"ref52","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2015","journal-title":"ICLRE"},{"key":"ref10","article-title":"Multiple object recognition with visual attention","author":"ba","year":"2015","journal-title":"ICLRE"},{"key":"ref11","article-title":"Learning to combine foveal glimpses with a third-order boltzmann machine","author":"larochelle","year":"2010","journal-title":"NIPS"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/IROS40897.2019.8967615"},{"key":"ref12","article-title":"Show, attend and tell: Neural image caption generation with visual attention","author":"xu","year":"2015","journal-title":"ICML"},{"key":"ref13","article-title":"Hierarchical question-image co-attention for visual question answering","author":"lu","year":"2016","journal-title":"NIPS"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.10"},{"key":"ref15","article-title":"Neural machine translation by jointly learning to align and translate","author":"bahdanau","year":"2015","journal-title":"ICLRE"},{"key":"ref16","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"NIPS"},{"key":"ref17","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"devlin","year":"2019","journal-title":"NAACL-HLT"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/S0042-6989(97)00169-7"},{"key":"ref19","article-title":"Cnvlutin2: Ineffectual-activation-and-weight-free deep neural network computing","author":"judd","year":"2017","journal-title":"CoRR"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00401"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00908"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/IROS40897.2019.8967743"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.39"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/34.730558"},{"journal-title":"Neurobiology of Attention","year":"2005","author":"itti","key":"ref7"},{"key":"ref49","article-title":"The concrete distribution: A continuous relaxation of discrete random variables","author":"maddison","year":"2017","journal-title":"ICLRE"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2009.5459462"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01157"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.21236\/ADA232947"},{"key":"ref48","article-title":"Categorical reparameterization with gumbel-softmax","author":"jang","year":"2017","journal-title":"ICLRE"},{"key":"ref47","article-title":"U-Net: Convolutional networks for biomedical image segmentation","author":"ronneberger","year":"2015","journal-title":"MICCAI"},{"key":"ref42","article-title":"Dsdnet: Deep structured self-driving network","author":"zeng","year":"2020","journal-title":"ECCV"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58592-1_25"},{"key":"ref44","article-title":"Risk-sensitive generative adversarial imitation learning","author":"lacotte","year":"2019","journal-title":"AISTATS"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1177\/0278364918772017"}],"event":{"name":"2021 IEEE International Conference on Robotics and Automation (ICRA)","start":{"date-parts":[[2021,5,30]]},"location":"Xi'an, China","end":{"date-parts":[[2021,6,5]]}},"container-title":["2021 IEEE International Conference on Robotics and Automation (ICRA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9560720\/9560666\/09561904.pdf?arnumber=9561904","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T11:47:05Z","timestamp":1652183225000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9561904\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,30]]},"references-count":53,"URL":"https:\/\/doi.org\/10.1109\/icra48506.2021.9561904","relation":{},"subject":[],"published":{"date-parts":[[2021,5,30]]}}}