Automatic Caption Generation for News Images

By Yansong Feng, Mirella Lapata. 2013

119 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Natural Language Processing, Multimodal Learning

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Citations in the corpus

Grounded Compositional Semantics for Finding and Describing Images with Sentences (2014, background): “Feng and Lapata (2013) use a large dataset of captioned images and experiments with both extractive (search) and abstractive (generation) models.”
Microsoft COCO Captions: Data Collection and Evaluation Server (2015, background): “The automatic generation of captions for images is a long standing and challenging problem in artiﬁcial intelligence [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19].”
ReferItGame: Referring to Objects in Photographs of Natural Scenes (2014, methodology): “Retrieval based methods (Aker and Gaizauskas, 2010; Farhadi et al., 2010; Ordonez et al., 2011; Feng and Lapata, 2010; Feng and Lapata, 2013) retrieve existing captions or phrases to describe a query image.”
TreeTalk: Composition and Compression of Trees for Image Descriptions (2014, background): “The second direction, in a complementary avenue to the first, has explored ways to make use of the rich spectrum of visual descriptions contributed by online citizens (Kuznetsova et al., 2012; Feng and Lapata, 2013; Mason, 2013; Ordonez et al., 2011).”
Joint Video and Text Parsing for Understanding Events and Answering Queries (2013, background): “…associated textual descriptions; Jia et al. [19] proposed a probabilistic model that encodes relations between loosely related images and text descriptions; Feng and Lapata [20] learned a probabilistic topic model of visual and textual words for the purpose of automatic image caption generation.”
Natural Language Models for Predicting Programming Comments (2013, background): “A related and well studied NLP task is that of predicting natural language caption and commentary for images and videos (Blei and Jordan, 2003; Feng and Lapata, 2010; Feng and Lapata, 2013; Wu and Li, 2011).”
From Show to Tell: A Survey on Deep Learning-Based Image Captioning (2021, background): “should be described [231], [232], and the rich journalistic style should be maintained [233], [234].”
Integrating Language and Vision to Generate Natural Language Descriptions of Videos in the Wild (2014, background): “Although there is a fair bit of research on generating naturallanguage descriptions of images (Feng and Lapata, 2013; Yang et al., 2011; Li et al., 2011; Ordonez et al., 2011), there is significantly less work on describing videos (Barbu et al., 2012; Guadarrama et al., 2013; Das et al., 2013;…”