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Found 4 papers, 2 papers with code
Open Set Domain Adaptation for Image and Action Recognition
Since this assumption is violated under real-world conditions, we propose an approach for open set domain adaptation where the target domain contains instances of categories that are not present in the source domain.
Mining YouTube - A dataset for learning fine-grained action concepts from webly supervised video data
Action recognition is so far mainly focusing on the problem of classification of hand selected preclipped actions and reaching impressive results in this field.
NeuralNetwork-Viterbi: A Framework for Weakly Supervised Video Learning
Video learning is an important task in computer vision and has experienced increasing interest over the recent years.
Recurrent Residual Learning for Action Recognition
In this work, we propose a novel recurrent ConvNet architecture called recurrent residual networks to address the task of action recognition.
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