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Guiding the Long-Short Term Memory Model for Image Caption Generation
2015
2015 IEEE International Conference on Computer Vision (ICCV)
In this work we focus on the problem of image caption generation. We propose an extension of the long short term memory (LSTM) model, which we coin gLSTM for short. In particular, we add semantic information extracted from the image as extra input to each unit of the LSTM block, with the aim of guiding the model towards solutions that are more tightly coupled to the image content. Additionally, we explore different length normalization strategies for beam search to avoid bias towards short
doi:10.1109/iccv.2015.277
dblp:conf/iccv/JiaGFT15
fatcat:zavbil3m6fdvljmtypczbn4exi