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文献紹介：Unsupervised Domain Adaptation for Spatio-Temporal Action Localization

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Toru Tamaki
Toru Tamaki

Nakul Agarwal, Yi-Ting Chen, Behzad Dariush and Ming-Hsuan Yang, "Unsupervised Domain Adaptation for Spatio-Temporal Action Localization", BMVC2020 https://www.bmvc2020-conference.com/assets/papers/0166.pdf https://www.bmvc2020-conference.com/programme/accepted-papers/

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Unsupervised Domain Adaptation for Spatio-Temporal Action Localization Nakul Agrawal, Yi-Ting Chen, Behzad Dariush, Ming-Husan Yang BMVC2020 大見一樹（名工大） 2022/10/28
概要 nSpatio-temporal action localization (STAL) の教師なしドメイン適応 • 著者によるとSTALに教師なしドメイン適応を用いた最初の研究 nSTALに有効な3つのドメイン適応モジュールの提案 !"#$%&'()*(+,+-./01.2234+56667879:
ドメイン適応 ソース ターゲット 教師なし ドメイン適応 ラベル なし ソースドメイン!"#の情報を使用して ターゲットドメイン（$）におけるタスクを解く ラベルがない（少ない）$の特徴量を ラベルがある"の特徴量に近づけることで $の適切な特徴量を獲得する ドメイン適応とは ドメインとは あるデータが持つ特有の傾向 今回の場合はデータの収集元が異なる ラベル あり
手法の概要 キーフレームで ドメイン適応 画像レベルで ドメイン適応 インスタンスレベルで ドメイン適応
モデルのベース キーフレームで ドメイン適応 画像レベルで ドメイン適応 インスタンスレベルで ドメイン適応 領域検出 任意のサイズの検出領域を 固定サイズにプーリング 検出対象のフレームである Key frameが入力される Key frameが中間フレームとなる クリップが入力される
Spatial Domain Classifier 画像レベルで ドメイン適応 インスタンスレベルで ドメイン適応 識別器の出力 損失 分類の難易度で重みづけ ドメインラベル キーフレームで ドメイン適応 逆伝播時に 勾配の符号を反転
Temporal Domain Classifier (Image) キーフレームで ドメイン適応 画像レベルで ドメイン適応 インスタンスレベルで ドメイン適応
Temporal Domain Classifier (Instance) キーフレームで ドメイン適応 画像レベルで ドメイン適応 インスタンスレベルで ドメイン適応 識別器の出力 損失
手法の概要 画像レベルで ドメイン適応 インスタンスレベルで ドメイン適応 キーフレームで ドメイン適応
実験設定 nデータセット • UCF101-Sports [Rodriguez+, CVPR2008] • JHMDB [Jhuang+, ICCV2013] • UCF101 [Soomro+, arXiv2012] nドメイン適応の設定 • UCF101-Sports → UCF101 (共通する4クラス) • JHMDB21 → UCF101 (共通する3クラス)
実験結果 nドメイン適応モジュールを3つ使うのが有効 UCF101-Sports → UCF101の結果 ドメイン適応なし ドメイン適応あり
実験結果 nドメイン適応モジュールを3つ使うのが有効 JHMDB → UCF101の結果 ドメイン適応なし ドメイン適応あり
まとめ nSpatio-temporal action localizationのドメイン適応手法を提案 • 3つのドメイン適応モジュールの有効性を実験的に示した

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