Matches in SemOpenAlex for { <https://semopenalex.org/work/W2789777740> ?p ?o ?g. }
Showing items 1 to 88 of
88
with 100 items per page.
- W2789777740 abstract "3D LiDARs and 2D cameras are increasingly being used alongside each other in sensor rigs for perception tasks. Before these sensors can be used to gather meaningful data, however, their extrinsics (and intrinsics) need to be accurately calibrated, as the performance of the sensor rig is extremely sensitive to these calibration parameters. A vast majority of existing calibration techniques require significant amounts of data and/or calibration targets and human effort, severely impacting their applicability in large-scale production systems. We address this gap with CalibNet: a self-supervised deep network capable of automatically estimating the 6-DoF rigid body transformation between a 3D LiDAR and a 2D camera in real-time. CalibNet alleviates the need for calibration targets, thereby resulting in significant savings in calibration efforts. During training, the network only takes as input a LiDAR point cloud, the corresponding monocular image, and the camera calibration matrix K. At train time, we do not impose direct supervision (i.e., we do not directly regress to the calibration parameters, for example). Instead, we train the network to predict calibration parameters that maximize the geometric and photometric consistency of the input images and point clouds. CalibNet learns to iteratively solve the underlying geometric problem and accurately predicts extrinsic calibration parameters for a wide range of mis-calibrations, without requiring retraining or domain adaptation. The project page is hosted at this https URL" @default.
- W2789777740 created "2018-03-29" @default.
- W2789777740 creator A5006222520 @default.
- W2789777740 creator A5021709131 @default.
- W2789777740 creator A5029303809 @default.
- W2789777740 creator A5075816776 @default.
- W2789777740 date "2018-03-22" @default.
- W2789777740 modified "2023-09-27" @default.
- W2789777740 title "CalibNet: Self-Supervised Extrinsic Calibration using 3D Spatial Transformer Networks." @default.
- W2789777740 cites W1575087183 @default.
- W2789777740 cites W1990398405 @default.
- W2789777740 cites W2115579991 @default.
- W2789777740 cites W2194775991 @default.
- W2789777740 cites W2200124539 @default.
- W2789777740 cites W2217105717 @default.
- W2789777740 cites W2295149141 @default.
- W2789777740 cites W2307770531 @default.
- W2789777740 cites W2489710028 @default.
- W2789777740 cites W2560609797 @default.
- W2789777740 cites W2560722161 @default.
- W2789777740 cites W2770841999 @default.
- W2789777740 cites W2963121255 @default.
- W2789777740 cites W2963270286 @default.
- W2789777740 cites W2964121744 @default.
- W2789777740 cites W2964314455 @default.
- W2789777740 cites W2435623039 @default.
- W2789777740 hasPublicationYear "2018" @default.
- W2789777740 type Work @default.
- W2789777740 sameAs 2789777740 @default.
- W2789777740 citedByCount "4" @default.
- W2789777740 countsByYear W27897777402019 @default.
- W2789777740 countsByYear W27897777402020 @default.
- W2789777740 crossrefType "posted-content" @default.
- W2789777740 hasAuthorship W2789777740A5006222520 @default.
- W2789777740 hasAuthorship W2789777740A5021709131 @default.
- W2789777740 hasAuthorship W2789777740A5029303809 @default.
- W2789777740 hasAuthorship W2789777740A5075816776 @default.
- W2789777740 hasConcept C105795698 @default.
- W2789777740 hasConcept C131979681 @default.
- W2789777740 hasConcept C154945302 @default.
- W2789777740 hasConcept C165838908 @default.
- W2789777740 hasConcept C205649164 @default.
- W2789777740 hasConcept C2908650547 @default.
- W2789777740 hasConcept C31972630 @default.
- W2789777740 hasConcept C33923547 @default.
- W2789777740 hasConcept C41008148 @default.
- W2789777740 hasConcept C51399673 @default.
- W2789777740 hasConcept C62649853 @default.
- W2789777740 hasConcept C65909025 @default.
- W2789777740 hasConceptScore W2789777740C105795698 @default.
- W2789777740 hasConceptScore W2789777740C131979681 @default.
- W2789777740 hasConceptScore W2789777740C154945302 @default.
- W2789777740 hasConceptScore W2789777740C165838908 @default.
- W2789777740 hasConceptScore W2789777740C205649164 @default.
- W2789777740 hasConceptScore W2789777740C2908650547 @default.
- W2789777740 hasConceptScore W2789777740C31972630 @default.
- W2789777740 hasConceptScore W2789777740C33923547 @default.
- W2789777740 hasConceptScore W2789777740C41008148 @default.
- W2789777740 hasConceptScore W2789777740C51399673 @default.
- W2789777740 hasConceptScore W2789777740C62649853 @default.
- W2789777740 hasConceptScore W2789777740C65909025 @default.
- W2789777740 hasLocation W27897777401 @default.
- W2789777740 hasOpenAccess W2789777740 @default.
- W2789777740 hasPrimaryLocation W27897777401 @default.
- W2789777740 hasRelatedWork W1499148156 @default.
- W2789777740 hasRelatedWork W2003565498 @default.
- W2789777740 hasRelatedWork W2295149141 @default.
- W2789777740 hasRelatedWork W2518401284 @default.
- W2789777740 hasRelatedWork W2773892280 @default.
- W2789777740 hasRelatedWork W2890102763 @default.
- W2789777740 hasRelatedWork W2908599206 @default.
- W2789777740 hasRelatedWork W2910454395 @default.
- W2789777740 hasRelatedWork W2944524499 @default.
- W2789777740 hasRelatedWork W2963270286 @default.
- W2789777740 hasRelatedWork W2963400571 @default.
- W2789777740 hasRelatedWork W2967040347 @default.
- W2789777740 hasRelatedWork W3103662244 @default.
- W2789777740 hasRelatedWork W3106441708 @default.
- W2789777740 hasRelatedWork W3133142895 @default.
- W2789777740 hasRelatedWork W3133630616 @default.
- W2789777740 hasRelatedWork W3175380624 @default.
- W2789777740 hasRelatedWork W3177989692 @default.
- W2789777740 hasRelatedWork W3205078851 @default.
- W2789777740 hasRelatedWork W3209216267 @default.
- W2789777740 isParatext "false" @default.
- W2789777740 isRetracted "false" @default.
- W2789777740 magId "2789777740" @default.
- W2789777740 workType "article" @default.