Wildlife recognition in nature documentaries with weak supervision from subtitles and external data
نویسندگان
چکیده
منابع مشابه
Wildlife recognition in nature documentaries with weak supervision from subtitles and external data
We propose a weakly supervised framework for domain adaptation in a multi-modal context for multi-label classification. This framework is applied to annotate objects such as animals in a target video with subtitles, in the absence of visual demarcators. We start from classifiers trained on external data (the source, in our setting ImageNet), and iteratively adapt them to the target dataset usin...
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We investigate animal recognition models learned from wildlife video documentaries by using the weak supervision of the textual subtitles. This is a challenging setting, since i) the animals occur in their natural habitat and are often largely occluded and ii) subtitles are to a great degree complementary to the visual content, providing a very weak supervisory signal. This is in contrast to mo...
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Real world images of objects belonging to a particular class typically show large variability in shape, appearance, scale, degree of occlusion, etc. Thus, a major challenge for generic object recognition is to develop object models that are flexible enough to accommodate these large intra-class variabilities. Such powerful models, in turn, require large amounts of training data to be effective ...
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ژورنال
عنوان ژورنال: Pattern Recognition Letters
سال: 2016
ISSN: 0167-8655
DOI: 10.1016/j.patrec.2016.01.025