{
  "id": 113895,
  "title": "Useful Papers/Blogs/References",
  "url": "/competitions/pku-autonomous-driving/discussion/113895",
  "author_name": "Bibek",
  "post_date": "2019-10-22T21:05:50.668000",
  "votes": 129,
  "comment_count": 26,
  "views": 0,
  "content": "<ol>\n<li><a href=\"https://justinyuzheng.com/research-6dof/\">6 DoF Vehicle Pose Estimation for Autonomous Racing</a></li>\n<li><a href=\"http://openaccess.thecvf.com/content_CVPRW_2019/papers/Autonomous%20Driving/Wu_6D-VNet_End-to-End_6-DoF_Vehicle_Pose_Estimation_From_Monocular_RGB_Images_CVPRW_2019_paper.pdf\">6D-VNet: End-to-end 6DoF Vehicle Pose Estimation from Monocular RGB Images</a></li>\n<li><a href=\"https://www.therobotreport.com/nvidia-grasping-system-synthetic-data/\">NVIDIA 6-DoF pose estimation trained on synthetic data</a></li>\n<li><a href=\"https://carsexplained.wordpress.com/2017/02/21/fundamentals-of-car-science-pitch-and-roll/\">Fundamentals of car science : Pitch, roll and yaw</a></li>\n<li><a href=\"https://medium.com/lyftlevel5/self-driving-research-in-review-icra-2019-digest-e914405fe598\">Self-driving Research in Review: ICRA 2019 Digest</a></li>\n<li><a href=\"https://sites.google.com/view/6packtracking/home\">6-PACK: Category-level 6D Pose Tracker with Anchor-Based Keypoints</a></li>\n<li><a href=\"https://github.com/stevenwudi/6DVNET\">6 DoF estimation network</a></li>\n<li><a href=\"http://apolloscape.auto/scene.html#to_standard_href\">ApolloScene Understanding</a></li>\n</ol>\n\n<p>This post will be updated as I find new useful references for this competition. </p>",
  "messages": [
    {
      "id": 655246,
      "postDate": "2019-10-22T21:05:50.667Z",
      "content": "<ol>\n<li><a href=\"https://justinyuzheng.com/research-6dof/\">6 DoF Vehicle Pose Estimation for Autonomous Racing</a></li>\n<li><a href=\"http://openaccess.thecvf.com/content_CVPRW_2019/papers/Autonomous%20Driving/Wu_6D-VNet_End-to-End_6-DoF_Vehicle_Pose_Estimation_From_Monocular_RGB_Images_CVPRW_2019_paper.pdf\">6D-VNet: End-to-end 6DoF Vehicle Pose Estimation from Monocular RGB Images</a></li>\n<li><a href=\"https://www.therobotreport.com/nvidia-grasping-system-synthetic-data/\">NVIDIA 6-DoF pose estimation trained on synthetic data</a></li>\n<li><a href=\"https://carsexplained.wordpress.com/2017/02/21/fundamentals-of-car-science-pitch-and-roll/\">Fundamentals of car science : Pitch, roll and yaw</a></li>\n<li><a href=\"https://medium.com/lyftlevel5/self-driving-research-in-review-icra-2019-digest-e914405fe598\">Self-driving Research in Review: ICRA 2019 Digest</a></li>\n<li><a href=\"https://sites.google.com/view/6packtracking/home\">6-PACK: Category-level 6D Pose Tracker with Anchor-Based Keypoints</a></li>\n<li><a href=\"https://github.com/stevenwudi/6DVNET\">6 DoF estimation network</a></li>\n<li><a href=\"http://apolloscape.auto/scene.html#to_standard_href\">ApolloScene Understanding</a></li>\n</ol>\n\n<p>This post will be updated as I find new useful references for this competition. </p>",
      "rawMarkdown": "1. [6 DoF Vehicle Pose Estimation for Autonomous Racing](https://justinyuzheng.com/research-6dof/)\n2. [6D-VNet: End-to-end 6DoF Vehicle Pose Estimation from Monocular RGB Images](http://openaccess.thecvf.com/content_CVPRW_2019/papers/Autonomous%20Driving/Wu_6D-VNet_End-to-End_6-DoF_Vehicle_Pose_Estimation_From_Monocular_RGB_Images_CVPRW_2019_paper.pdf)\n3. [NVIDIA 6-DoF pose estimation trained on synthetic data](https://www.therobotreport.com/nvidia-grasping-system-synthetic-data/)\n4. [Fundamentals of car science : Pitch, roll and yaw](https://carsexplained.wordpress.com/2017/02/21/fundamentals-of-car-science-pitch-and-roll/)\n5. [Self-driving Research in Review: ICRA 2019 Digest](https://medium.com/lyftlevel5/self-driving-research-in-review-icra-2019-digest-e914405fe598)\n6. [6-PACK: Category-level 6D Pose Tracker with Anchor-Based Keypoints](https://sites.google.com/view/6packtracking/home)\n7. [6 DoF estimation network](https://github.com/stevenwudi/6DVNET)\n8. [ApolloScene Understanding](http://apolloscape.auto/scene.html#to_standard_href)\n\nThis post will be updated as I find new useful references for this competition. ",
      "votes": 127
    },
    {
      "id": 657562,
      "postDate": "2019-10-25T08:41:44.960Z",
      "content": "<p>Wow, I saw my paper here. Very excited to know that my paper got some exposure ：）</p>",
      "rawMarkdown": "Wow, I saw my paper here. Very excited to know that my paper got some exposure ：）",
      "votes": 15,
      "replies": [
        {
          "id": 675546,
          "postDate": "2019-11-18T07:55:33.733Z",
          "content": "<p>Your paper and code is something from which I am trying to learn the concept . Thanks a lot .</p>",
          "rawMarkdown": "Your paper and code is something from which I am trying to learn the concept . Thanks a lot .",
          "votes": 1
        }
      ]
    },
    {
      "id": 656640,
      "postDate": "2019-10-24T13:46:29.133Z",
      "content": "<p>Thanks a lot for sharing these resources!</p>",
      "rawMarkdown": "Thanks a lot for sharing these resources!",
      "votes": 1
    },
    {
      "id": 656549,
      "postDate": "2019-10-24T11:32:18.530Z",
      "content": "<p>Thank you so much. Although I still don't know how to start.</p>",
      "rawMarkdown": "Thank you so much. Although I still don't know how to start.",
      "votes": 1,
      "replies": [
        {
          "id": 656560,
          "postDate": "2019-10-24T11:50:40.617Z",
          "content": "<p>Maybe start by downloading the data and do some EDA and think about how to model the problem</p>",
          "rawMarkdown": "Maybe start by downloading the data and do some EDA and think about how to model the problem",
          "votes": 2
        }
      ]
    },
    {
      "id": 661653,
      "postDate": "2019-10-30T14:52:43.400Z",
      "content": "<p>Thanks for kind sharing!!\nI just found <a href=\"https://arxiv.org/pdf/1812.11788v1.pdf\">PVNet</a>. Is this also a good starting point?</p>",
      "rawMarkdown": "Thanks for kind sharing!!\nI just found [PVNet](https://arxiv.org/pdf/1812.11788v1.pdf). Is this also a good starting point?",
      "votes": 2,
      "replies": [
        {
          "id": 664785,
          "postDate": "2019-11-04T08:13:39.593Z",
          "content": "<p>PVNet has the best performance on some datasets, you can try it.</p>",
          "rawMarkdown": "PVNet has the best performance on some datasets, you can try it.",
          "votes": 1
        }
      ]
    },
    {
      "id": 686403,
      "postDate": "2019-12-03T05:36:17.617Z",
      "content": "<p>I'm new in object detection, after exploration in the Internet, I make a summary about algorithm of object detection. \n<a href=\"https://www.kaggle.com/c/pku-autonomous-driving/discussion/120015\">https://www.kaggle.com/c/pku-autonomous-driving/discussion/120015</a></p>",
      "rawMarkdown": "I'm new in object detection, after exploration in the Internet, I make a summary about algorithm of object detection. \nhttps://www.kaggle.com/c/pku-autonomous-driving/discussion/120015"
    },
    {
      "id": 656222,
      "postDate": "2019-10-24T02:51:30.987Z",
      "content": "<p>thansk for sharing!!!👍 </p>",
      "rawMarkdown": "thansk for sharing!!!👍 "
    },
    {
      "id": 655585,
      "postDate": "2019-10-23T08:13:20.037Z",
      "content": "<p>I see you everywhere~~~</p>",
      "rawMarkdown": "I see you everywhere~~~",
      "replies": [
        {
          "id": 655596,
          "postDate": "2019-10-23T08:31:18.697Z",
          "content": "<p>because I choose to be a Kaggler fulltime 😜 </p>",
          "rawMarkdown": "because I choose to be a Kaggler fulltime 😜 ",
          "votes": 7
        }
      ]
    },
    {
      "id": 686629,
      "postDate": "2019-12-03T11:06:30.483Z",
      "rawMarkdown": "",
      "isDeleted": true
    },
    {
      "id": 658534,
      "postDate": "2019-10-26T06:01:05.033Z",
      "rawMarkdown": "",
      "isDeleted": true
    },
    {
      "id": 655333,
      "postDate": "2019-10-22T23:40:25.677Z",
      "content": "<p>thanks you</p>",
      "rawMarkdown": "thanks you",
      "votes": 1
    },
    {
      "id": 655359,
      "postDate": "2019-10-23T01:18:19.940Z",
      "content": "<p>cool sources. thanks for sharing!💪 </p>",
      "rawMarkdown": "cool sources. thanks for sharing!💪 ",
      "votes": 2
    },
    {
      "id": 655366,
      "postDate": "2019-10-23T01:28:26.467Z",
      "content": "<p>thanks for sharing.</p>",
      "rawMarkdown": "thanks for sharing."
    },
    {
      "id": 691543,
      "postDate": "2019-12-10T08:47:10.910Z",
      "content": "<p>Thanks for sharing</p>",
      "rawMarkdown": "Thanks for sharing"
    },
    {
      "id": 686477,
      "postDate": "2019-12-03T07:46:26.317Z",
      "content": "<p>Thanks a lot.</p>",
      "rawMarkdown": "Thanks a lot."
    },
    {
      "id": 685345,
      "postDate": "2019-12-01T13:21:43.043Z",
      "content": "<p>Thanks  a lot for sharing!</p>",
      "rawMarkdown": "Thanks  a lot for sharing!"
    },
    {
      "id": 681090,
      "postDate": "2019-11-25T16:44:34.457Z",
      "content": "<p>thanks for sharing!</p>",
      "rawMarkdown": "thanks for sharing!"
    },
    {
      "id": 664349,
      "postDate": "2019-11-03T14:37:00.150Z",
      "content": "<p>Very useful, thank you!</p>",
      "rawMarkdown": "Very useful, thank you!"
    },
    {
      "id": 657406,
      "postDate": "2019-10-25T05:41:36.523Z",
      "content": "<p>Thanks!</p>",
      "rawMarkdown": "Thanks!"
    },
    {
      "id": 656244,
      "postDate": "2019-10-24T03:33:25.090Z",
      "content": "<p>It's great! Thanks for sharing.</p>",
      "rawMarkdown": "It's great! Thanks for sharing."
    },
    {
      "id": 655966,
      "postDate": "2019-10-23T18:14:46.630Z",
      "content": "<p>thanks</p>",
      "rawMarkdown": "thanks"
    },
    {
      "id": 655765,
      "postDate": "2019-10-23T13:33:02.850Z",
      "content": "<p>thanks you</p>",
      "rawMarkdown": "thanks you"
    },
    {
      "id": 655549,
      "postDate": "2019-10-23T06:59:04.470Z",
      "content": "<p>Thanks for sharing!</p>",
      "rawMarkdown": "Thanks for sharing!"
    }
  ],
  "comments": [
    {
      "id": 657562,
      "author_name": "stevenwudi",
      "author_url": "",
      "post_date": "2019-10-25T08:41:44.960000",
      "content": "<p>Wow, I saw my paper here. Very excited to know that my paper got some exposure ：）</p>",
      "votes": 15,
      "replies": [
        {
          "id": 675546,
          "author_name": "Nirjhar Roy",
          "author_url": "",
          "post_date": "2019-11-18T07:55:33.733000",
          "content": "<p>Your paper and code is something from which I am trying to learn the concept . Thanks a lot .</p>",
          "votes": 1,
          "replies": []
        }
      ]
    },
    {
      "id": 656640,
      "author_name": "Ayush GUPTA",
      "author_url": "",
      "post_date": "2019-10-24T13:46:29.133000",
      "content": "<p>Thanks a lot for sharing these resources!</p>",
      "votes": 1,
      "replies": []
    },
    {
      "id": 656549,
      "author_name": "leontp",
      "author_url": "",
      "post_date": "2019-10-24T11:32:18.530000",
      "content": "<p>Thank you so much. Although I still don't know how to start.</p>",
      "votes": 1,
      "replies": [
        {
          "id": 656560,
          "author_name": "Bibek",
          "author_url": "",
          "post_date": "2019-10-24T11:50:40.617000",
          "content": "<p>Maybe start by downloading the data and do some EDA and think about how to model the problem</p>",
          "votes": 2,
          "replies": []
        }
      ]
    },
    {
      "id": 661653,
      "author_name": "Terence",
      "author_url": "",
      "post_date": "2019-10-30T14:52:43.400000",
      "content": "<p>Thanks for kind sharing!!\nI just found <a href=\"https://arxiv.org/pdf/1812.11788v1.pdf\">PVNet</a>. Is this also a good starting point?</p>",
      "votes": 2,
      "replies": [
        {
          "id": 664785,
          "author_name": "Linye Li",
          "author_url": "",
          "post_date": "2019-11-04T08:13:39.593000",
          "content": "<p>PVNet has the best performance on some datasets, you can try it.</p>",
          "votes": 1,
          "replies": []
        }
      ]
    },
    {
      "id": 686403,
      "author_name": "DiegoJohnson",
      "author_url": "",
      "post_date": "2019-12-03T05:36:17.617000",
      "content": "<p>I'm new in object detection, after exploration in the Internet, I make a summary about algorithm of object detection. \n<a href=\"https://www.kaggle.com/c/pku-autonomous-driving/discussion/120015\">https://www.kaggle.com/c/pku-autonomous-driving/discussion/120015</a></p>",
      "votes": 0,
      "replies": []
    },
    {
      "id": 656222,
      "author_name": "MrDemons",
      "author_url": "",
      "post_date": "2019-10-24T02:51:30.987000",
      "content": "<p>thansk for sharing!!!👍 </p>",
      "votes": 0,
      "replies": []
    },
    {
      "id": 655585,
      "author_name": "Tian",
      "author_url": "",
      "post_date": "2019-10-23T08:13:20.037000",
      "content": "<p>I see you everywhere~~~</p>",
      "votes": 0,
      "replies": [
        {
          "id": 655596,
          "author_name": "Bibek",
          "author_url": "",
          "post_date": "2019-10-23T08:31:18.697000",
          "content": "<p>because I choose to be a Kaggler fulltime 😜 </p>",
          "votes": 7,
          "replies": []
        }
      ]
    },
    {
      "id": 686629,
      "author_name": "",
      "author_url": "",
      "post_date": "2019-12-03T11:06:30.483000",
      "content": "",
      "votes": 0,
      "replies": []
    },
    {
      "id": 658534,
      "author_name": "",
      "author_url": "",
      "post_date": "2019-10-26T06:01:05.033000",
      "content": "",
      "votes": 0,
      "replies": []
    },
    {
      "id": 655333,
      "author_name": "nguyenvantui",
      "author_url": "",
      "post_date": "2019-10-22T23:40:25.677000",
      "content": "<p>thanks you</p>",
      "votes": 1,
      "replies": []
    },
    {
      "id": 655359,
      "author_name": "Adrian Zinovei",
      "author_url": "",
      "post_date": "2019-10-23T01:18:19.940000",
      "content": "<p>cool sources. thanks for sharing!💪 </p>",
      "votes": 2,
      "replies": []
    },
    {
      "id": 655366,
      "author_name": "Tarek Hamdi",
      "author_url": "",
      "post_date": "2019-10-23T01:28:26.467000",
      "content": "<p>thanks for sharing.</p>",
      "votes": 0,
      "replies": []
    },
    {
      "id": 691543,
      "author_name": "Swathy Murali Mohan",
      "author_url": "",
      "post_date": "2019-12-10T08:47:10.910000",
      "content": "<p>Thanks for sharing</p>",
      "votes": 0,
      "replies": []
    },
    {
      "id": 686477,
      "author_name": "hedaobaishui",
      "author_url": "",
      "post_date": "2019-12-03T07:46:26.317000",
      "content": "<p>Thanks a lot.</p>",
      "votes": 0,
      "replies": []
    },
    {
      "id": 685345,
      "author_name": "Kranti Kumar",
      "author_url": "",
      "post_date": "2019-12-01T13:21:43.043000",
      "content": "<p>Thanks  a lot for sharing!</p>",
      "votes": 0,
      "replies": []
    },
    {
      "id": 681090,
      "author_name": "neo. w",
      "author_url": "",
      "post_date": "2019-11-25T16:44:34.457000",
      "content": "<p>thanks for sharing!</p>",
      "votes": 0,
      "replies": []
    },
    {
      "id": 664349,
      "author_name": "Rafael Mosca",
      "author_url": "",
      "post_date": "2019-11-03T14:37:00.150000",
      "content": "<p>Very useful, thank you!</p>",
      "votes": 0,
      "replies": []
    },
    {
      "id": 657406,
      "author_name": "跟着丞相割麦子",
      "author_url": "",
      "post_date": "2019-10-25T05:41:36.523000",
      "content": "<p>Thanks!</p>",
      "votes": 0,
      "replies": []
    },
    {
      "id": 656244,
      "author_name": "",
      "author_url": "",
      "post_date": "2019-10-24T03:33:25.090000",
      "content": "<p>It's great! Thanks for sharing.</p>",
      "votes": 0,
      "replies": []
    },
    {
      "id": 655966,
      "author_name": "darthgera123",
      "author_url": "",
      "post_date": "2019-10-23T18:14:46.630000",
      "content": "<p>thanks</p>",
      "votes": 0,
      "replies": []
    },
    {
      "id": 655765,
      "author_name": "Eevee",
      "author_url": "",
      "post_date": "2019-10-23T13:33:02.850000",
      "content": "<p>thanks you</p>",
      "votes": 0,
      "replies": []
    },
    {
      "id": 655549,
      "author_name": "Hieu Phung",
      "author_url": "",
      "post_date": "2019-10-23T06:59:04.470000",
      "content": "<p>Thanks for sharing!</p>",
      "votes": 0,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "655246": "1. [6 DoF Vehicle Pose Estimation for Autonomous Racing](https://justinyuzheng.com/research-6dof/)\n2. [6D-VNet: End-to-end 6DoF Vehicle Pose Estimation from Monocular RGB Images](http://openaccess.thecvf.com/content_CVPRW_2019/papers/Autonomous%20Driving/Wu_6D-VNet_End-to-End_6-DoF_Vehicle_Pose_Estimation_From_Monocular_RGB_Images_CVPRW_2019_paper.pdf)\n3. [NVIDIA 6-DoF pose estimation trained on synthetic data](https://www.therobotreport.com/nvidia-grasping-system-synthetic-data/)\n4. [Fundamentals of car science : Pitch, roll and yaw](https://carsexplained.wordpress.com/2017/02/21/fundamentals-of-car-science-pitch-and-roll/)\n5. [Self-driving Research in Review: ICRA 2019 Digest](https://medium.com/lyftlevel5/self-driving-research-in-review-icra-2019-digest-e914405fe598)\n6. [6-PACK: Category-level 6D Pose Tracker with Anchor-Based Keypoints](https://sites.google.com/view/6packtracking/home)\n7. [6 DoF estimation network](https://github.com/stevenwudi/6DVNET)\n8. [ApolloScene Understanding](http://apolloscape.auto/scene.html#to_standard_href)\n\nThis post will be updated as I find new useful references for this competition. ",
    "657562": "Wow, I saw my paper here. Very excited to know that my paper got some exposure ：）",
    "656640": "Thanks a lot for sharing these resources!",
    "656549": "Thank you so much. Although I still don't know how to start.",
    "661653": "Thanks for kind sharing!!\nI just found [PVNet](https://arxiv.org/pdf/1812.11788v1.pdf). Is this also a good starting point?",
    "686403": "I'm new in object detection, after exploration in the Internet, I make a summary about algorithm of object detection. \nhttps://www.kaggle.com/c/pku-autonomous-driving/discussion/120015",
    "656222": "thansk for sharing!!!👍 ",
    "655585": "I see you everywhere~~~",
    "686629": "",
    "658534": "",
    "655333": "thanks you",
    "655359": "cool sources. thanks for sharing!💪 ",
    "655366": "thanks for sharing.",
    "691543": "Thanks for sharing",
    "686477": "Thanks a lot.",
    "685345": "Thanks  a lot for sharing!",
    "681090": "thanks for sharing!",
    "664349": "Very useful, thank you!",
    "657406": "Thanks!",
    "656244": "It's great! Thanks for sharing.",
    "655966": "thanks",
    "655765": "thanks you",
    "655549": "Thanks for sharing!"
  }
}