About ApolloScape Dataset

Trajectory dataset, 3D Perception Lidar Object Detection and Tracking dataset including about 100K image frames, 80k lidar point cloud and 1000km trajectories for urban traffic. The dataset consisting of varying conditions and traffic densities which includes many challenging scenarios where vehicles, bicycles, and pedestrians move among one another. Please checkout toolkit on Github Toolkit for ApolloScape Dataset

Learn more
Scene Parsing

The whole dataset will include RGB videos with high resolution image sequences and per pixel annotation, survey-grade dense 3D points with semantic segmentation. Our continuous collection will further add more sensors, such as stereoscopic video and panoramic images; and cover a wide range of environment, weather, and traffic conditions. Scene Parsing dataset provides 146,997 frames with corresponding pixel-level annotations and pose information, depth maps for static background.

Learn more
News
Publication
  • DVI: Depth Guided Video Inpainting for Autonomous Driving.
    Miao Liao, Feixiang Lu, Dingfu Zhou, Sibo Zhang, Wei Li, and Ruigang Yang. European Conference on Computer Vision. ECCV 2020
    [PDF]   [Inpainting Dataset]   [Github]   [Result Video]   [Presentation Video]   [BibTex]
  • TrafficPredict: Trajectory Prediction for Heterogeneous Traffic-Agents.
    Yuexin Ma, Xinge Zhu, Sibo Zhang, Ruigang Yang, Wenping Wang, and Dinesh Manocha. The Thirty-Third AAAI Conference on Artificial Intelligence. AAAI 2019 (oral)
    [PDF]   [Trajectory Dataset]   [Github]   [Webpage]   [Video]   [BibTex]
  • The apolloscape open dataset for autonomous driving and its application.
    Huang, Xinyu and Wang, Peng and Cheng, Xinjing and Zhou, Dingfu and Geng, Qichuan and Yang, Ruigang. IEEE transactions on pattern analysis and machine intelligence
    [PDF]   [Scene Dataset]   [BibTex]
  • ApolloCar3D: A Large 3D Car Instance Understanding Benchmark for Autonomous Driving.
    Song, Xibin and Wang, Peng and Zhou, Dingfu and Zhu, Rui and Guan, Chenye and Dai, Yuchao and Su, Hao and Li, Hongdong and Yang, Ruigang. CVPR, 2019
    [PDF]   [Car Instance Dataset]   [BibTex]
  • AADS: Augmented autonomous driving simulation using data-driven algorithms.
    Wei Li, Chengwei Pan, Rong Zhang, Jiaping Ren, Yuexin Ma, Jin Fang, Feilong Yan, Qichuan Geng, Xinyu Huang, Huajun Gong, Weiwei Xu, Guoping Wang, Dinesh Manocha, Ruigang Yang. Science Robotics, 2019
    [PDF]
Dataset Update
  • Top Toolkit for ApolloScape Dataset
  • 2020.09 Released Inpainting Dataset, consists of synchronized Labeled image and LiDAR scanned point clouds.
  • 2019.03 Released 3D Lidar Object Detection and Tracking Dataset, contains 80k lidar point cloud for urban traffic
  • 2019.02 Released Trajectory Dataset, contains 1000km trajectories for urban traffic.
  • 2018.03.08 We have released the first part of the dataset that contains 74555 video frames and their pixel-level and instance-level annotations
  • 2018.03.21 We added the second part of the data set, including 43592 depth images for static background (road01_ins_depth&road02_ins_depth)
  • 2018.03.29 Update the data set, including 30,963 depth images for static background (road03_ins_depth和road04_ins_depth)
  • 2018.03.30 Update the data set, including 22,871 pixel-level images and depth images for static background (road02_seg和road02_seg_depth)
  • 2018.03.30 Uploaded the Image lists for training, validation, and testing for road01_ins, road02_ins, and road03_ins
  • 2018.04.03 Update the data set, including 49,571 pixel-level images and depth images for static background(road03_seg and road04_seg)
  • 2018.04.03 Scene Parsing data set cumulatively provides 146,997 frames with corresponding pixel-level annotations and pose information,depth maps for static background.
ApolloScape
Autonomous Driving Forefront Technology And Datasets
About ApolloScape Dataset
    Trajectory dataset, 3D Perception Lidar Object Detection and Tracking dataset including about 100K image frames, 80k lidar point cloud and 1000km trajectories for urban traffic. The dataset consisting of varying conditions and traffic densities which includes many challenging scenarios where vehicles, bicycles, and pedestrians move among one another. Please checkout toolkit on Github Toolkit for ApolloScape Dataset
Scene Parsing
    The whole dataset will include RGB videos with high resolution image sequences and per pixel annotation, survey-grade dense 3D points with semantic segmentation. Our continuous collection will further add more sensors, such as stereoscopic video and panoramic images; and cover a wide range of environment, weather, and traffic conditions. Scene Parsing dataset provides 146,997 frames with corresponding pixel-level annotations and pose information, depth maps for static background.
News
Publication
  • DVI: Depth Guided Video Inpainting for Autonomous Driving.
    Miao Liao, Feixiang Lu, Dingfu Zhou, Sibo Zhang, Wei Li, and Ruigang Yang. European Conference on Computer Vision. ECCV 2020
    [PDF]   [Inpainting Dataset]   [Github]   [Result Video]   [Presentation Video]   [BibTex]
  • TrafficPredict: Trajectory Prediction for Heterogeneous Traffic-Agents.
    Yuexin Ma, Xinge Zhu, Sibo Zhang, Ruigang Yang, Wenping Wang, and Dinesh Manocha. The Thirty-Third AAAI Conference on Artificial Intelligence. AAAI 2019 (oral)
    [PDF]   [Trajectory Dataset]   [Github]   [Webpage]   [Video]   [BibTex]
  • The apolloscape open dataset for autonomous driving and its application.
    Huang, Xinyu and Wang, Peng and Cheng, Xinjing and Zhou, Dingfu and Geng, Qichuan and Yang, Ruigang. IEEE transactions on pattern analysis and machine intelligence
    [PDF]   [Scene Dataset]   [BibTex]
  • ApolloCar3D: A Large 3D Car Instance Understanding Benchmark for Autonomous Driving.
    Song, Xibin and Wang, Peng and Zhou, Dingfu and Zhu, Rui and Guan, Chenye and Dai, Yuchao and Su, Hao and Li, Hongdong and Yang, Ruigang. CVPR, 2019
    [PDF]   [Car Instance Dataset]   [BibTex]
  • AADS: Augmented autonomous driving simulation using data-driven algorithms.
    Wei Li, Chengwei Pan, Rong Zhang, Jiaping Ren, Yuexin Ma, Jin Fang, Feilong Yan, Qichuan Geng, Xinyu Huang, Huajun Gong, Weiwei Xu, Guoping Wang, Dinesh Manocha, Ruigang Yang. Science Robotics, 2019
    [PDF]
Dataset Update
  • Top Toolkit for ApolloScape Dataset
  • 2020.09 Released Inpainting Dataset, consists of synchronized Labeled image and LiDAR scanned point clouds.
  • 2019.03 Released 3D Lidar Object Detection and Tracking Dataset, contains 80k lidar point cloud for urban traffic
  • 2019.02 Released Trajectory Dataset, contains 1000km trajectories for urban traffic.
  • 2018.03.08 We have released the first part of the dataset that contains 74555 video frames and their pixel-level and instance-level annotations
  • 2018.03.21 We added the second part of the data set, including 43592 depth images for static background (road01_ins_depth&road02_ins_depth)
  • 2018.03.29 Update the data set, including 30,963 depth images for static background (road03_ins_depth和road04_ins_depth)
  • 2018.03.30 Update the data set, including 22,871 pixel-level images and depth images for static background (road02_seg和road02_seg_depth)
  • 2018.03.30 Uploaded the Image lists for training, validation, and testing for road01_ins, road02_ins, and road03_ins
  • 2018.04.03 Update the data set, including 49,571 pixel-level images and depth images for static background(road03_seg and road04_seg)
  • 2018.04.03 Scene Parsing data set cumulatively provides 146,997 frames with corresponding pixel-level annotations and pose information,depth maps for static background.