2020年4月14日 · To this end, we release the Audi Autonomous Driving Dataset (A2D2). Our dataset consists of simultaneously recorded images and 3D point clouds, together with 3D bounding boxes, semantic segmentation, instance segmentation, and …

Audi Autonomous Driving Dataset (A2D2) consists of simultaneously recorded images and 3D point clouds, together with 3D bounding boxes, semantic segmentation, instance segmentation, and data extracted from the automotive bus.

2020年4月15日 · 今天奥迪公司的研究人员在发布的论文 A2D2: Audi Autonomous Driving Dataset 中，公布了其大型 自动驾驶 数据集A2D2，并提供开放下载。 目标为推进 计算机视觉 、 机器学习 、自动驾驶的商用和学术研究。 即包含RGB图像，也包括对应的3D点云数据，记录的数据是时间同步的。 目标3D包围框，语义分割，实例分割以及从汽车总线提取的数据。 6 个摄像头和 5 个Velodyne VLP-16 LiDAR 传感器，对车辆周围环境360覆盖。 标注的非序列数据，41227帧， …

A2Dimage is a scripted 3ds Max plug-in for adding simple 2D images with alpha channel to your 3ds Max scene. Script reads the height of the image from the end of the file name and on render generates automatically shadows based on alpha channel of the image.

15K annotated video clips supplemented with over 4M annotated images in the following categories: bikes, books, bottles, cameras, cereal boxes, chairs, cups, laptops, and shoes, manually annotated 3D bounding boxes for each object

Please cite as follows: @article{geyer2020a2d2, title={{A2D2: Audi Autonomous Driving Dataset}}, author={Jakob Geyer and Yohannes Kassahun and Mentar Mahmudi and Xavier Ricou and Rupesh Durgesh and Andrew S. Chung and Lorenz Hauswald and Viet Hoang Pham and Maximilian M{\"u}hlegg and Sebastian Dorn and Tiffany Fernandez and Martin J{\"a}nicke and Sudesh Mirashi and Chiragkumar Savani and ...

A2Dre is a subset from the A2D test set including $433$~\textit{non-trivial} REs. Due to its highly unbalanced distribution across the $7$~semantic categories we select the $4$~major categories \textsl{appearance, location, motion and static}.

The A2D dataset serves as a large-scale testbed for various vision problems: video-level single- and multiple-label actor-action recognition, instance-level object segmentation/co-segmentation, as well as pixel-level actor-action semantic segmentation to name a few.

A2D: A Dataset and Benchmark for Action Recognition and Segmentation with Multiple Classes of Actors Authors: Chenliang Xu and Jason J. Corso Email: {cliangxu,jjcorso}@umich.edu URL: http://web.eecs.umich.edu/~jjcorso/r/a2d Date: 06/01/2015 Version: 1.0 If you use the dataset, cite the following reference: [1] Can Humans Fly?

Only AVOD hosts are whitelisted, and the Composed Images service is no longer supported as an origin. The purpose of a decoupled implementation is to provide portability. The implementation transforms the incoming URL parameters to an imquery that is passed on to the default IM policy.