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We investigate how to iteratively and mutually boost object classification and detection performance by taking the outputs from one task as the context of the other one. While context models have been quite popular, previous works mainly concentrate onco-occurrence relationship within classes and few of them focus on contextualization from a top-down perspective, i.e. high-level task context. In this...
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