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Recognizing arbitrary objects in the wild has been a challenging problem due to the limitations of existing classification models and datasets. In this paper, we propose a new task that aims at parsing scenes with a large and open vocabulary, and several evaluation metrics are explored for this problem. Our approach is a joint image pixel and word concept embeddings framework, where word concepts...
This paper describes an online place discovery and recognition engine that fuses information over time to create topologically distinct places. A key motivation is the recognition that a single image may be a poor exemplar of what constitutes a place. Images are not ‘places’ nor are they ‘documents’. Instead, by treating image-sequences as a multimodal distribution over topics — and by discovering...
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