{
  "id": 177194,
  "title": "GANs for predicting trajectory",
  "url": "/competitions/lyft-motion-prediction-autonomous-vehicles/discussion/177194",
  "author_name": "Sirish Somanchi",
  "post_date": "2020-08-25T06:13:20.795000",
  "votes": 19,
  "comment_count": 0,
  "views": 0,
  "content": "<p>How <a href=\"https://arxiv.org/abs/2004.06247\" target=\"_blank\">Uber SC-GAN</a> successfully predicted cars’ movements even in somewhat challenging edge cases and <a href=\"https://analyticsindiamag.com/how-uber-outperformed-existing-gans-based-baselines-in-self-driving-cars/\" target=\"_blank\">outperformed existing GANs-Based Baselines</a> In Self-Driving Cars (<a href=\"https://arxiv.org/pdf/2004.06247.pdf\" target=\"_blank\">Paper</a>)</p>\n<p>Other GANs for predicting motion:</p>\n<ul>\n<li><a href=\"https://github.com/agrimgupta92/sgan\" target=\"_blank\">Social GAN</a> (<a href=\"https://arxiv.org/abs/1803.10892\" target=\"_blank\">paper</a>)</li>\n<li><a href=\"https://github.com/crowdbotp/socialways\" target=\"_blank\">Social Ways</a> (<a href=\"https://arxiv.org/abs/1904.09507\" target=\"_blank\">paper</a>)</li>\n<li><a href=\"https://github.com/StanfordVL/sophie\" target=\"_blank\">SoPhie</a> (<a href=\"https://arxiv.org/abs/1806.01482\" target=\"_blank\">paper</a>)</li>\n<li><a href=\"http://papers.neurips.cc/paper/8308-social-bigat-multimodal-trajectory-forecasting-using-bicycle-gan-and-graph-attention-networks.pdf\" target=\"_blank\">Social-BiGAT</a>: Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networks</li>\n</ul>",
  "messages": [
    {
      "id": 984519,
      "postDate": "2020-08-25T06:13:20.797Z",
      "content": "<p>How <a href=\"https://arxiv.org/abs/2004.06247\" target=\"_blank\">Uber SC-GAN</a> successfully predicted cars’ movements even in somewhat challenging edge cases and <a href=\"https://analyticsindiamag.com/how-uber-outperformed-existing-gans-based-baselines-in-self-driving-cars/\" target=\"_blank\">outperformed existing GANs-Based Baselines</a> In Self-Driving Cars (<a href=\"https://arxiv.org/pdf/2004.06247.pdf\" target=\"_blank\">Paper</a>)</p>\n<p>Other GANs for predicting motion:</p>\n<ul>\n<li><a href=\"https://github.com/agrimgupta92/sgan\" target=\"_blank\">Social GAN</a> (<a href=\"https://arxiv.org/abs/1803.10892\" target=\"_blank\">paper</a>)</li>\n<li><a href=\"https://github.com/crowdbotp/socialways\" target=\"_blank\">Social Ways</a> (<a href=\"https://arxiv.org/abs/1904.09507\" target=\"_blank\">paper</a>)</li>\n<li><a href=\"https://github.com/StanfordVL/sophie\" target=\"_blank\">SoPhie</a> (<a href=\"https://arxiv.org/abs/1806.01482\" target=\"_blank\">paper</a>)</li>\n<li><a href=\"http://papers.neurips.cc/paper/8308-social-bigat-multimodal-trajectory-forecasting-using-bicycle-gan-and-graph-attention-networks.pdf\" target=\"_blank\">Social-BiGAT</a>: Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networks</li>\n</ul>",
      "rawMarkdown": "How [Uber SC-GAN](https://arxiv.org/abs/2004.06247) successfully predicted cars’ movements even in somewhat challenging edge cases and [outperformed existing GANs-Based Baselines](https://analyticsindiamag.com/how-uber-outperformed-existing-gans-based-baselines-in-self-driving-cars/) In Self-Driving Cars ([Paper](https://arxiv.org/pdf/2004.06247.pdf))\n\nOther GANs for predicting motion:\n- [Social GAN](https://github.com/agrimgupta92/sgan) ([paper](https://arxiv.org/abs/1803.10892))\n- [Social Ways](https://github.com/crowdbotp/socialways) ([paper](https://arxiv.org/abs/1904.09507))\n- [SoPhie](https://github.com/StanfordVL/sophie) ([paper](https://arxiv.org/abs/1806.01482))\n- [Social-BiGAT](http://papers.neurips.cc/paper/8308-social-bigat-multimodal-trajectory-forecasting-using-bicycle-gan-and-graph-attention-networks.pdf): Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networks",
      "votes": 19
    }
  ],
  "comments": [],
  "raw_markdown_by_id": {
    "984519": "How [Uber SC-GAN](https://arxiv.org/abs/2004.06247) successfully predicted cars’ movements even in somewhat challenging edge cases and [outperformed existing GANs-Based Baselines](https://analyticsindiamag.com/how-uber-outperformed-existing-gans-based-baselines-in-self-driving-cars/) In Self-Driving Cars ([Paper](https://arxiv.org/pdf/2004.06247.pdf))\n\nOther GANs for predicting motion:\n- [Social GAN](https://github.com/agrimgupta92/sgan) ([paper](https://arxiv.org/abs/1803.10892))\n- [Social Ways](https://github.com/crowdbotp/socialways) ([paper](https://arxiv.org/abs/1904.09507))\n- [SoPhie](https://github.com/StanfordVL/sophie) ([paper](https://arxiv.org/abs/1806.01482))\n- [Social-BiGAT](http://papers.neurips.cc/paper/8308-social-bigat-multimodal-trajectory-forecasting-using-bicycle-gan-and-graph-attention-networks.pdf): Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networks"
  }
}