DeepIR: A Deep Semantics Driven Framework for Image Retargeting

Autor:	Lin, Jianxin, Zhou, Tiankuang, Chen, Zhibo
Rok vydání:	2018
Předmět:	Computer Science - Computer Vision and Pattern Recognition
Druh dokumentu:	Working Paper
Popis:	We present \emph{Deep Image Retargeting} (\emph{DeepIR}), a coarse-to-fine framework for content-aware image retargeting. Our framework first constructs the semantic structure of input image with a deep convolutional neural network. Then a uniform re-sampling that suits for semantic structure preserving is devised to resize feature maps to target aspect ratio at each feature layer. The final retargeting result is generated by coarse-to-fine nearest neighbor field search and step-by-step nearest neighbor field fusion. We empirically demonstrate the effectiveness of our model with both qualitative and quantitative results on widely used RetargetMe dataset. Comment: 8 pages, 10 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1811.07793 Zobrazit plný text záznamu View this record from Arxiv