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Bird's-Eye-View (BEV) semantic maps have become an essential component of automated driving pipelines due to the rich representation they provide for decision-making tasks.
Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography
Martin A Fischler and Robert C Bolles · 1981
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Inverse perspective mapping simplifies optical flow computation and obstacle detection
Hanspeter A Mallot, Heinrich H Bülthoff, JJ Little, and Stefan Bohrer · 1991
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Geometric context from a single image
Derek Hoiem, Alexei A Efros, and Martial Hebert · 2005
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Accurate, dense, and robust multiview stereopsis
Yasutaka Furukawa and Jean Ponce · 2009
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Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
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Structure-from-motion revisited
Johannes L Schonberger and Jan-Michael Frahm · 2016
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Simple does it: Weakly supervised instance and semantic segmentation
Anna Khoreva, Rodrigo Benenson, Jan Hosang, Matthias Hein, and Bernt Schiele · 2017
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DBSCAN revisited, revisited: why and how you should (still) use DBSCAN
Erich Schubert, Jörg Sander, Martin Ester, Hans Peter Kriegel, and Xiaowei Xu · 2017
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Learning latent representations of 3d human pose with deep neural networks
Isinsu Katircioglu, Bugra Tekin, Mathieu Salzmann, Vincent Lepetit, and Pascal Fua · 2018
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Learning to look around objects for top-view representations of outdoor scenes
Samuel Schulter, Menghua Zhai, Nathan Jacobs, and Manmohan Chandraker · 2018
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Digging into self-supervised monocular depth estimation
Clément Godard, Oisin Mac Aodha, Michael Firman, and Gabriel J Brostow · 2019
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Scaling and benchmarking self-supervised visual representation learning
Priya Goyal, Dhruv Mahajan, Abhinav Gupta, and Ishan Misra · 2019
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Deepvio: Self-supervised deep learning of monocular visual inertial odometry using 3d geometric constraints
Liming Han, Yimin Lin, Guoguang Du, and Shiguo Lian · 2019
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Selflow: Self-supervised learning of optical flow
Pengpeng Liu, Michael Lyu, Irwin King, and Jia Xu · 2019
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Monocular semantic occupancy grid mapping with convolutional variational encoder–decoder networks
Chenyang Lu, Marinus Jacobus Gerardus van de Molengraft, and Gijs Dubbelman · 2019
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3d packing for self-supervised monocular depth estimation
Vitor Guizilini, Rares Ambrus, Sudeep Pillai, Allan Raventos, and Adrien Gaidon · 2020
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Self-supervised monocular scene flow estimation
Junhwa Hur and Stefan Roth · 2020
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Flow2stereo: Effective self-supervised learning of optical flow and stereo matching
Pengpeng Liu, Irwin King, Michael R Lyu, and Jia Xu · 2020
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Weakly supervised 3d object detection from lidar point cloud
Qinghao Meng, Wenguan Wang, Tianfei Zhou, Jianbing Shen, Luc Van Gool, and Dengxin Dai · 2020
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BEV-Seg: Bird’s eye view semantic segmentation using geometry and semantic point cloud
Mong Him Ng, Kaahan Radia, Jianfei Chen, Dequan Wang, Ionel Gog, and Joey Gonzalez · 2020
Cited alongside, same era.
Cross-view semantic segmentation for sensing surroundings
Self-supervised learning of depth inference for multi-view stereo
Jiayu Yang, Jose M Alvarez, and Miaomiao Liu · 2021
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Dynamic object removal and spatio-temporal rgb-d inpainting via geometry-aware adversarial learning
Borna Bešić and Abhinav Valada · 2022
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Vit-bevseg: A hierarchical transformer network for monocular birds-eye-view segmentation
Pramit Dutta, Ganesh Sistu, Senthil Yogamani, Edgar Galván, and John McDonald · 2022
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Bird’s-eye-view panoptic segmentation using monocular frontal view images
Nikhil Gosala and Abhinav Valada · 2022
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Semantic scene segmentation for robotics
Juana Valeria Hurtado and Abhinav Valada · 2022
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Bowen Pan, Jiankai Sun, Ho Yin Tiga Leung, Alex Andonian, and Bolei Zhou · 2020
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Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d
Jonah Philion and Sanja Fidler · 2020
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Predicting semantic map representations from images using pyramid occupancy networks
Thomas Roddick and Roberto Cipolla · 2020
Cited alongside, same era.
Scalability in perception for autonomous driving: Waymo open dataset
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, et al · 2020
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Efficientdet: Scalable and efficient object detection
Mingxing Tan, Ruoming Pang, and Quoc V Le · 2020
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Learning kinematic feasibility for mobile manipulation through deep reinforcement learning
Daniel Honerkamp, Tim Welschehold, and Abhinav Valada · 2021
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From learning to relearning: A framework for diminishing bias in social robot navigation
Juana Valeria Hurtado, Laura Londoño, and Abhinav Valada · 2021
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Qi Li, Yue Wang, Yilun Wang, and Hang Zhao · 2022
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Kitti-360: A novel dataset and benchmarks for urban scene understanding in 2d and 3d
Yiyi Liao, Jun Xie, and Andreas Geiger · 2022
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Bevfusion: Multi-task multi-sensor fusion with unified bird’s-eye view representation
Zhijian Liu, Haotian Tang, Alexander Amini, Xinyu Yang, Huizi Mao, Daniela Rus, and Song Han · 2022
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Underwater enhancement based on a self-learning strategy and attention mechanism for high-intensity regions
Claudio Mello Jr, Bryan Moreira, Paulo Evald, Paulo Drews-Jr, and Silvia Botelho · 2022
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Translating images into maps
Avishkar Saha, Oscar Mendez, Chris Russell, and Richard Bowden · 2022
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Continual slam: Beyond lifelong simultaneous localization and mapping through continual learning
Niclas Vödisch, Daniele Cattaneo, Wolfram Burgard, and Abhinav Valada · 2022
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Self-supervised learning of multi-object keypoints for robotic manipulation
Jan Ole von Hartz, Eugenio Chisari, Tim Welschehold, and Abhinav Valada · 2022
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Cross-view transformers for real-time map-view semantic segmentation
Brady Zhou and Philipp Krähenbühl · 2022
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Catch me if you hear me: Audio-visual navigation in complex unmapped environments with moving sounds
Abdelrahman Younes, Daniel Honerkamp, Tim Welschehold, and Abhinav Valada · 2023
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