Deep Boosting: Joint Feature Selection and Analysis Dictionary Learning in Hierarchy

no code implementations • 8 Aug 2015 • Zhanglin Peng, Ya Li, Zhaoquan Cai, Liang Lin

In each layer, we construct a dictionary of filters by combining the filters from the lower layer, and iteratively optimize the image representation with a joint discriminative-generative formulation, i. e. minimization of empirical classification error plus regularization of analysis image generation over training images.

Classification Dictionary Learning +4

Data-Driven Scene Understanding with Adaptively Retrieved Exemplars

no code implementations • 3 Feb 2015 • Xionghao Liu, Wei Yang, Liang Lin, Qing Wang, Zhaoquan Cai, Jian-Huang Lai

In the first step, the references are selected by jointly matching their appearances with the target as well as the semantics (i. e. the assigned labels of the target and the references).

Scene Understanding Semantic Segmentation +1