Title:
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Temporal activity detection in untrimmed videos with recurrent neural networks
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Author:
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Montes, Alberto; Salvador Aguilera, Amaia; Pascual, Santiago; Giró Nieto, Xavier
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Other authors:
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Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions; Universitat Politècnica de Catalunya. GPI - Grup de Processament d'Imatge i Vídeo |
Abstract:
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This work proposes a simple pipeline to classify and temporally localize activities in untrimmed videos. Our system uses features from a 3D Convolutional Neural Network (C3D) as input to train a a recurrent neural network (RNN) that learns to classify video clips of 16 frames. After clip prediction, we post-process the output of the RNN to assign a single activity label to each video, and determine the temporal boundaries of the activity within the video. We show how our system can achieve competitive results in both tasks with a simple architecture. We evaluate our method in the ActivityNet Challenge 2016, achieving a 0.5874 mAP and a 0.2237 mAP in the classification and detection tasks, respectively. Our code and models are publicly available at: https://imatge-upc.github.io/activitynet-2016-cvprw/ |
Abstract:
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Peer Reviewed |
Subject(s):
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-Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial -Computer vision -Pattern recognition systems -Neural networks (Computer science) -Visió per ordinador -Reconeixement de formes (Informàtica) -Xarxes neuronals (Informàtica) |
Rights:
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Document type:
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Article - Published version Conference Object |
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