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3D-BEVIS: Birds-Eye-View Instance Segmentation [article]

Cathrin Elich, Francis Engelmann, Jonas Schult, Theodora Kontogianni,, Bastian Leibe
2019 arXiv   pre-print
Therefore, we propose to combine local point geometry with global context information from an intermediate bird's-eye view representation.  ...  In this work, we present 3D-BEVIS, a deep learning framework for 3D semantic instance segmentation on point clouds.  ...  Left to Right: Input bird's-eye view B, ground truth instance labels, predicted instance features B colored according to the GT instance labels.  ... 
arXiv:1904.02199v2 fatcat:5g6wnkxrtbavlokekbkl2hvltu

FIERY: Future Instance Prediction in Bird's-Eye View from Surround Monocular Cameras [article]

Anthony Hu, Zak Murez, Nikhil Mohan, Sofía Dudas, Jeffrey Hawke, Vijay Badrinarayanan, Roberto Cipolla, Alex Kendall
2021 arXiv   pre-print
We present FIERY: a probabilistic future prediction model in bird's-eye view from monocular cameras.  ...  Our model predicts future instance segmentation and motion of dynamic agents that can be transformed into non-parametric future trajectories.  ...  and form the bird's-eye view instance segmentation (Figure 3f ).  ... 
arXiv:2104.10490v3 fatcat:3n6fhnw6andt3l4skutgbptwca

Frustum PointNets for 3D Object Detection from RGB-D Data [article]

Charles R. Qi, Wei Liu, Chenxia Wu, Hao Su, Leonidas J. Guibas
2018 arXiv   pre-print
While previous methods focus on images or 3D voxels, often obscuring natural 3D patterns and invariances of 3D data, we directly operate on raw point clouds by popping up RGB-D scans.  ...  In this work, we study 3D object detection from RGB-D data in both indoor and outdoor scenes.  ...  Bird's eye view based methods: MV3D [6] projects Li-DAR point cloud to bird's eye view and trains a region proposal network (RPN [29] ) for 3D bounding box proposal.  ... 
arXiv:1711.08488v2 fatcat:aatdkha3gzgcnoe4rpem6fggaa

Frustum PointNets for 3D Object Detection from RGB-D Data

Charles R. Qi, Wei Liu, Chenxia Wu, Hao Su, Leonidas J. Guibas
2018 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition  
While previous methods focus on images or 3D voxels, often obscuring natural 3D patterns and invariances of 3D data, we directly operate on raw point clouds by popping up RGB-D scans.  ...  In this work, we study 3D object detection from RGB-D data in both indoor and outdoor scenes.  ...  Bird's eye view based methods: MV3D [5] projects Li-DAR point cloud to bird's eye view and trains a region proposal network (RPN [23] ) for 3D bounding box proposal.  ... 
doi:10.1109/cvpr.2018.00102 dblp:conf/cvpr/QiLWSG18 fatcat:za5o64qpcrgqvijmioux6clnpq

HDMapNet: An Online HD Map Construction and Evaluation Framework [article]

Qi Li, Yue Wang, Yilun Wang, Hang Zhao
2022 arXiv   pre-print
HDMapNet encodes image features from surrounding cameras and/or point clouds from LiDAR, and predicts vectorized map elements in the bird's-eye view.  ...  In addition, we develop semantic-level and instance-level metrics to evaluate the map learning performance. Finally, we showcase our method is capable of predicting a locally consistent map.  ...  IPM: the lane segmentation result in the perspective view and the bird's-eye view. Others: the semantic segmentation results and the vectorized instance detection results.  ... 
arXiv:2107.06307v4 fatcat:dyzicwdkxjfjjlm3uavfg37i6i

Multi Projection Fusion for Real-time Semantic Segmentation of 3D LiDAR Point Clouds [article]

Yara Ali Alnaggar, Mohamed Afifi, Karim Amer, Mohamed Elhelw
2020 arXiv   pre-print
Our Multi-Projection Fusion (MPF) framework analyzes spherical and bird's-eye view projections using two separate highly-efficient 2D fully convolutional models then combines the segmentation results of  ...  Semantic segmentation of 3D point cloud data is essential for enhanced high-level perception in autonomous platforms.  ...  images for the bird's-eye view.  ... 
arXiv:2011.01974v2 fatcat:6dl2gcbninfypgfw2vxt736noy

Lift, Splat, Shoot: Encoding Images From Arbitrary Camera Rigs by Implicitly Unprojecting to 3D [article]

Jonah Philion, Sanja Fidler
2020 arXiv   pre-print
On standard bird's-eye-view tasks such as object segmentation and map segmentation, our model outperforms all baselines and prior work.  ...  We propose a new end-to-end architecture that directly extracts a bird's-eye-view representation of a scene given image data from an arbitrary number of cameras.  ...  For the object segmentation tasks, we obtain ground truth bird's-eye-view targets by projecting 3D bounding boxes into the bird's-eye-view plane.  ... 
arXiv:2008.05711v1 fatcat:pu2oi5kegvcuzf4uheobouixa4

SynWoodScape: Synthetic Surround-view Fisheye Camera Dataset for Autonomous Driving [article]

Ahmed Rida Sekkat, Yohan Dupuis, Varun Ravi Kumar, Hazem Rashed, Senthil Yogamani, Pascal Vasseur, Paul Honeine
2022 arXiv   pre-print
However, this means that multi-camera algorithms cannot be designed to obtain a unified output in birds-eye space, which is enabled in the new dataset.  ...  Surround-view cameras are a primary sensor for automated driving, used for near-field perception.  ...  bird's eye view and front view perspective images.  ... 
arXiv:2203.05056v3 fatcat:rtb7zulzwvhhrkncv3iuhxe7q4

CPGNet: Cascade Point-Grid Fusion Network for Real-Time LiDAR Semantic Segmentation [article]

Xiaoyan Li, Gang Zhang, Hongyu Pan, Zhenhua Wang
2022 arXiv   pre-print
Recent 2D projection-based methods, including range view and multi-view fusion, can run in real time, but suffer from lower accuracy due to information loss during the 2D projection.  ...  LiDAR semantic segmentation essential for advanced autonomous driving is required to be accurate, fast, and easy-deployed on mobile platforms.  ...  For instance, the point that is beyond the range of bird's-eye view, but in the range of range view, has meaningful features from range view.  ... 
arXiv:2204.09914v3 fatcat:hfzj7ilpyjfdffeazcsk7lsviy

FVNet: 3D Front-View Proposal Generation for Real-Time Object Detection from Point Clouds [article]

Jie Zhou, Xin Tan, Zhiwei Shao, Lizhuang Ma
2019 arXiv   pre-print
Instead of generating proposals from camera images or bird's-eye-view maps, we first project point clouds onto a cylindrical surface to generate front-view feature maps which retains rich information.  ...  It consists of two stages: generation of front-view proposals and estimation of 3D bounding box parameters.  ...  and bird's-eye-view maps.  ... 
arXiv:1903.10750v3 fatcat:htpvcfs5qrbo5bdkan6lckqagq

Cityscapes 3D: Dataset and Benchmark for 9 DoF Vehicle Detection [article]

Nils Gählert, Nicolas Jourdan, Marius Cordts, Uwe Franke, Joachim Denzler
2020 arXiv   pre-print
In order to ease multitask learning, we provide a pairing of 2D instance segments with 3D bounding boxes.  ...  To this end, we propose Cityscapes 3D, extending the original Cityscapes dataset with 3D bounding box annotations for all types of vehicles.  ...  Figure 5 . 5 bounding box annotation projected into the RGB image (b) Corresponding bird's-eye view labeling aid Example for bird's-eye view labeling aid. 3D bounding box annotations and the stereo point  ... 
arXiv:2006.07864v1 fatcat:kw6sebiwjjajtflbw7gvt7ytxm

MonoLayout: Amodal scene layout from a single image [article]

Kaustubh Mani, Swapnil Daga, Shubhika Garg, N. Sai Shankar, Krishna Murthy Jatavallabhula, K. Madhava Krishna
2020 arXiv   pre-print
Given a single color image captured from a driving platform, we aim to predict the bird's-eye view layout of the road and other traffic participants.  ...  Due to the lack of fair baseline methods, we extend several state-of-the-art approaches for road-layout estimation and vehicle occupancy estimation in bird's-eye view to the amodal setup for rigorous evaluation  ...  Specifically, we use disparity estimates from stereo cameras, semantic and instance segmentation labels, to segment and identify unique cars in bird's eye view.  ... 
arXiv:2002.08394v1 fatcat:etpsk24dtbgtzaoioouxiaueme

Vision-based navigation and environmental representations with an omnidirectional camera

J. Gaspar, N. Winters, J. Santos-Victor
2000 IEEE Transactions on Robotics and Automation  
The geometry of the catadioptric sensor and the method used to obtain a bird's eye (orthographic) view of the ground plane are presented.  ...  The robot is controlled to follow a pre-specified path accurately, by tracking visual landmarks in bird's eye views of the ground plane.  ...  Fig. 8 . 8 Left -Bird's eye view of the corridor.  ... 
doi:10.1109/70.897802 fatcat:ktlt5i3s5zaoha32w5bv5kfmeq

BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation [article]

Zhijian Liu, Haotian Tang, Alexander Amini, Xinyu Yang, Huizi Mao, Daniela Rus, Song Han
2022 arXiv   pre-print
It unifies multi-modal features in the shared bird's-eye view (BEV) representation space, which nicely preserves both geometric and semantic information.  ...  It establishes the new state of the art on nuScenes, achieving 1.3% higher mAP and NDS on 3D object detection and 13.6% higher mIoU on BEV map segmentation, with 1.9x lower computation cost.  ...  We would like to thank Xuanyao Chen and Brady Zhou for their guidance on detection and segmentation evaluation, and Yingfei Liu and Tiancai Wang for their helpful discussions.  ... 
arXiv:2205.13542v2 fatcat:qtunylgozjcvrdrjzdk23xjpve

Monocular 3D Object Detection with Pseudo-LiDAR Point Cloud [article]

Xinshuo Weng, Kris Kitani
2019 arXiv   pre-print
Through our evaluation on the KITTI benchmark, we achieve the top-ranked performance on both bird's eye view and 3D object detection among all monocular methods, effectively quadrupling the performance  ...  with its corresponding 2D proposal after projecting onto the image; (2) use the instance mask instead of the bounding box as the representation of 2D proposals, in order to reduce the number of points  ...  Additional Visualization of 3D Object Detection Results We provide additional qualitative results in Figure 4 .  ... 
arXiv:1903.09847v4 fatcat:vwqdxubedzddnkeuos6eqqgsny
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