[PDF] Top 20 On the Role of Scene Graphs in Image Captioning
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On the Role of Scene Graphs in Image Captioning
... as image captioning, is a long stand- ing problem in computer vision and computational ...of scene graphs has the potential to improve cap- tioning systems beyond current ... See full document
6
Meshed-Memory Transformer for Image Captioning
... the image encoding side, in- stead, single-layer attention mechanisms have been adopted to incorporate spatial knowledge, initially from a grid of CNN features [43, 24, 48], and then using image regions ... See full document
10
Object Counts! Bringing Explicit Detections Back into Image Captioning
... to image captioning – which used to constitute an essential stage in early work – is often bypassed in the currently dom- inant end-to-end approaches, where the lan- guage model is conditioned directly on a ... See full document
14
Aesthetic Image Captioning from Weakly Labelled Photographs
... evaluating image caption- ing such as BLEU (B) [62], METEOR (M) [7], ROGUE (R) [40], CIDEr (C) [78] ...compares scene graphs computed from the candidate and reference ... See full document
11
Visual Saliency for Image Captioning in New Multimedia Services
... the role of saliency prediction in image captioning architec- ...of image captions gener- ated by our method on the COCO Dataset [1], along with the corresponding visual saliency ... See full document
6
SubICap: Towards Subword-informed Image Captioning
... Figure 1. Our proposed model, which uses subword information, generates better captions compared to the baseline, which operates at the word-level. This example shows captions generated by our model and the baseline for ... See full document
10
Panoptic segmentation-based attention for image captioning
... important role in image captioning, as they provide the context information (scene, location, ...the image and provide the feature of brick wall to the captioning ...the ... See full document
18
Image Retrieval Using Image Captioning
... Therefore, image retrieval systems play a major role in fetching images relevant to the query provided by the ...image captioning. This report aims at understanding the purpose of image ... See full document
69
Compositional Generalization in Image Captioning
... We select pairs of concepts that are likely to be represented in an image recognition model. In par- ticular, we identify adjectives, nouns, and verbs in the English COCO captions dataset (Chen et al., 2015) that ... See full document
12
Pragmatically Informative Image Captioning with Character Level Inference
... Margaret Mitchell, Jesse Dodge, Amit Goyal, Kota Ya- maguchi, Karl Stratos, Xufeng Han, Alyssa Mensch, Alex Berg, Tamara Berg, and Hal Daume III. 2012. Midge: Generating image descriptions from com- puter vision ... See full document
5
Language Models for Image Captioning: The Quirks and What Works
... Two recent approaches have achieved state-of-the-art results in image caption- ing. The first uses a pipelined process where a set of candidate words is gen- erated by a convolutional neural network (CNN) trained ... See full document
6
Temporal difference Learning with Sampling Baseline for Image Captioning
... Inspired by the machine translation domain, recent works focus on the deep network based and end-to-end method- s mainly under the encoder-decoder framework. In general, the recurrent neural networks (RNN), especially ... See full document
8
Informative Image Captioning with External Sources of Information
... Table 2 shows the performance of our model. Using both image and input labels improves per- formance on all metrics, compared to the base- lines in Table 1. This indicates the effectiveness of our multi-encoder, ... See full document
10
Nonparametric Method for Data driven Image Captioning
... Although BLEU (Papineni et al., 2002) scores are widely used for image caption evaluation, we find them to be poor indicators of the quality of our model. As shown in Figure 1, our system’s BLEU scores increase ... See full document
7
Scene Image Classification and Retrieval
... to image descrip- tion, such as compactness of image representation, scalability of feature dimensions, invariance to rotation, image size, aspect ratio among others, colour feature of any kind would ... See full document
110
Improving Image Captioning with Conditional Generative Adversarial Nets
... Recently, the most popular generative model–generative adversarial nets (GANs) (Goodfellow et al. 2014)–has achieved great success in computer vision tasks. But un- like the deterministic continuous mapping from random ... See full document
9
Guided Open Vocabulary Image Captioning with Constrained Beam Search
... Our approach to out-of-domain image captioning could be applied to any existing CNN-RNN cap- tioning model that can be decoding using beam search, e.g., (Donahue et al., 2015; Mao et al., 2015; Karpathy and ... See full document
10
Can Neural Image Captioning be Controlled via Forced Attention?
... and α ∈ [0, 1] is guaranteed like in the implemen- tation of Xu et al. (2015). An important detail is that no value is actually zero. The model is still al- lowed to include image aspects outside the boxes for the ... See full document
5
Does Multimodality Help Human and Machine for Translation and Image Captioning?
... The experiment was performed by 16 native Ger- man speakers proficient in English with age rang- ing from 23 to 54 (coming from Austria, Germany and Switzerland, of which 10 are female and 6 male). The experiment is ... See full document
7
Bridging by Word: Image Grounded Vocabulary Construction for Visual Captioning
... visual captioning usu- ally employs a CNN-RNN architecture that combines a CNN for image encoding with a RNN for caption generation, where the vo- cabulary is constructed from the entire train- ing dataset ... See full document
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