IvaNet: Learning to jointly detect and segment objets with the help of Local Top-Down Modules
Shihua Huang,
Lu Wang
Abstract:Driven by Convolutional Neural Networks, object detection and semantic segmentation have gained significant improvements. However, existing methods on the basis of a full top-down module have limited robustness in handling those two tasks simultaneously. To this end, we present a joint multi-task framework, termed IvaNet. Different from existing methods, our IvaNet backwards abstract semantic information from higher layers to augment lower layers using local top-down modules. The comparisons against some count… Show more
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