<commit_before>{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "x8Q7Un821X1A"
      },
      "source": [
        "##### Copyright 2018 The TensorFlow Hub Authors.\n",
        "\n",
        "Licensed under the Apache License, Version 2.0 (the \"License\");"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "1W4rIAFt1Ui3"
      },
      "outputs": [],
      "source": [
        "# Copyright 2018 The TensorFlow Hub Authors. All Rights Reserved.\n",
        "#\n",
        "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
        "# you may not use this file except in compliance with the License.\n",
        "# You may obtain a copy of the License at\n",
        "#\n",
        "#     http://www.apache.org/licenses/LICENSE-2.0\n",
        "#\n",
        "# Unless required by applicable law or agreed to in writing, software\n",
        "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
        "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
        "# See the License for the specific language governing permissions and\n",
        "# limitations under the License.\n",
        "# =============================================================================="
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cDq0CIKc1vO_"
      },
      "source": [
        "# 使用膨胀 3D CNN 进行动作识别\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MfBg1C5NB3X0"
      },
      "source": [
        "<table class=\"tfo-notebook-buttons\" align=\"left\">\n",
        "  <td><a target=\"_blank\" href=\"https://www.tensorflow.org/hub/tutorials/action_recognition_with_tf_hub\"><img src=\"https://www.tensorflow.org/images/tf_logo_32px.png\">在 TensorFlow.org 上查看</a></td>\n",
        "  <td><a target=\"_blank\" href=\"https://colab.research.google.com/github/tensorflow/hub/blob/master/examples/colab/action_recognition_with_tf_hub.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\">在 Google Colab 中运行</a></td>\n",
        "  <td><a target=\"_blank\" href=\"https://github.com/tensorflow/hub/blob/master/examples/colab/action_recognition_with_tf_hub.ipynb\"><img src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\">在 GitHub 上查看源代码</a></td>\n",
        "  <td><a href=\"https://storage.googleapis.com/tensorflow_docs/hub/examples/colab/action_recognition_with_tf_hub.ipynb\"><img src=\"https://www.tensorflow.org/images/download_logo_32px.png\">下载笔记本</a></td>\n",
        "</table>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "h6W3FhoP3TxC"
      },
      "source": [
        "此 Colab 演示了如何使用 [tfhub.dev/deepmind/i3d-kinetics-400/1](https://tfhub.dev/deepmind/i3d-kinetics-400/1) 模块从视频数据进行动作识别。\n",
        "\n",
        "<NAME> 和 <NAME> 在其论文“[Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset](https://arxiv.org/abs/1705.07750)”中对底层模型进行了介绍。该论文于 2017 年 5 月在 arXiv 上发表，并被选为 CVPR 2017 会议论文。源代码已在 [GitHub](https://github.com/deepmind/kinetics-i3d) 上公开。\n",
        "\n",
        "“<NAME>”介绍了一种用于视频分类的新架构，即膨胀 3D 卷积神经网络或 I3D。此架构通过对上述模型进行微调，在 UCF101 和 HMDB51 数据集上取得了目前最优秀的结果。在 Kinetics 上预训练的 I3D 模型也在 CVPR 2017 [Charades 挑战](http://vuchallenge.org/charades.html)中排名第一。\n",
        "\n",<commit_msg>nblint fix<commit_after>{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "x8Q7Un821X1A"
      },
      "source": [
        "##### Copyright 2018 The TensorFlow Hub Authors.\n",
        "\n",
        "Licensed under the Apache License, Version 2.0 (the \"License\");"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "1W4rIAFt1Ui3"
      },
      "outputs": [],
      "source": [
        "# Copyright 2018 The TensorFlow Hub Authors. All Rights Reserved.\n",
        "#\n",
        "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
        "# you may not use this file except in compliance with the License.\n",
        "# You may obtain a copy of the License at\n",
        "#\n",
        "#     http://www.apache.org/licenses/LICENSE-2.0\n",
        "#\n",
        "# Unless required by applicable law or agreed to in writing, software\n",
        "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
        "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
        "# See the License for the specific language governing permissions and\n",
        "# limitations under the License.\n",
        "# =============================================================================="
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cDq0CIKc1vO_"
      },
      "source": [
        "# 使用膨胀 3D CNN 进行动作识别\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MfBg1C5NB3X0"
      },
      "source": [
        "<table class=\"tfo-notebook-buttons\" align=\"left\">\n",
        "  <td><a target=\"_blank\" href=\"https://tensorflow.google.cn/hub/tutorials/action_recognition_with_tf_hub\"><img src=\"https://tensorflow.google.cn/images/tf_logo_32px.png\">在 TensorFlow.org 上查看</a></td>\n",
        "  <td><a target=\"_blank\" href=\"https://colab.research.google.com/github/tensorflow/hub/blob/master/examples/colab/action_recognition_with_tf_hub.ipynb\"><img src=\"https://tensorflow.google.cn/images/colab_logo_32px.png\">在 Google Colab 中运行</a></td>\n",
        "  <td><a target=\"_blank\" href=\"https://github.com/tensorflow/hub/blob/master/examples/colab/action_recognition_with_tf_hub.ipynb\"><img src=\"https://tensorflow.google.cn/images/GitHub-Mark-32px.png\">在 GitHub 上查看源代码</a></td>\n",
        "  <td><a href=\"https://storage.googleapis.com/tensorflow_docs/hub/examples/colab/action_recognition_with_tf_hub.ipynb\"><img src=\"https://tensorflow.google.cn/images/download_logo_32px.png\">下载笔记本</a></td>\n",
        "</table>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "h6W3FhoP3TxC"
      },
      "source": [
        "此 Colab 演示了如何使用 [tfhub.dev/deepmind/i3d-kinetics-400/1](https://tfhub.dev/deepmind/i3d-kinetics-400/1) 模块从视频数据进行动作识别。\n",
        "\n",
        "<NAME> 和 <NAME> 在其论文“[Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset](https://arxiv.org/abs/1705.07750)”中对底层模型进行了介绍。该论文于 2017 年 5 月在 arXiv 上发表，并被选为 CVPR 2017 会议论文。源代码已在 [GitHub](https://github.com/deepmind/kinetics-i3d) 上公开。\n",
        "\n",
        "“Quo Vadis”介绍了一种用于视频分类的新架构，即膨胀 3D 卷积神经网络或 I3D。此架构通过对上述模型进行微调，在 UCF101 和 HMDB51 数据集上取得了目前最优秀的结果。在 Kinetics 上预训练的 I3D 模型也在 CVPR 2017 [Charades 挑战](http://vuchallenge.org/charades.html)中排名第一。\n",
        "\n",
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