[PDF] Top 20 Multi grained Attention with Object level Grounding for Visual Question Answering
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Multi grained Attention with Object level Grounding for Visual Question Answering
... of object-level groundings leads to a better understanding of the images and locates the attended objects more pre- ...for question “Can you see its paws?”, the attention generated by our ... See full document
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Segmentation Guided Attention Networks for Visual Question Answering
... provides object level groundings in the form of bounding boxes for the objects occuring in the ...561,459 object groundings from 36,579 cat- ...complete grounding annotations that link the ... See full document
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Dynamic Capsule Attention for Visual Question Answering
... of attention mechanism has been studied in many works (Tang, Srivas- tava, and Salakhutdinov 2014; Ba, Mnih, and Kavukcuoglu 2014; Mnih et ...The attention mechanism was further introduced to the task of ... See full document
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Visual TTR Modelling Visual Question Answering in Type Theory with Records
... Visual question answering is a recent popular task in the field of computer ...a visual and linguistic ...includes object recognition in the form of You Only Look Once (YOLO, Redmon et ... See full document
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Beyond RNNs: Positional Self-Attention with Co-Attention for Video Question Answering
... image-based question-answering, existing question- answering methods are mainly focusing on using a LSTM network to encode question sequence and fusing question representation ... See full document
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Decoupled Box Proposal and Featurization with Ultrafine Grained Semantic Labels Improve Image Captioning and Visual Question Answering
... with object boundaries have gained momentum (Fu et ...on Visual Genome. As both Visual Genome and VQA2 were built on images from MSCOCO, the object detector was applied largely to in-domain ... See full document
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Human Attention in Visual Question Answering: Do Humans and Deep Networks look at the same regions?
... zon Mechanical Turk (AMT). While (Jiang et al., 2015) studies natural exploration and collects task- independent human annotations by asking subjects to freely move the mouse cursor to anywhere they wanted to look on a ... See full document
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Differential Networks for Visual Question Answering
... Existing attention models focusing on fusion can be di- vided into two categories, linear models and bilinear ...and question feature el- ements, (Li and Jia 2016; Nam, Ha, and Kim 2017) used the ... See full document
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Multi Granularity Hierarchical Attention Fusion Networks for Reading Comprehension and Question Answering
... between question and passage; (ii) A multi-granularity attention mechanism applied at the word and sentence-level, enabling it to prop- erly attend to the most important content when ... See full document
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Cross-Modal Multistep Fusion Network with Co-Attention for Visual Question Answering
... As for fusion strategies, it is intuitive to use linear pooling approach to achieve multi-modal feature fusion. Although these approaches, such as element-wise addition and concatenation, are easy to implement, ... See full document
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Generating Question Relevant Captions to Aid Visual Question Answering
... generated question-relevant captions help the model to focus on more relevant objects via atten- tion adjustment, we compare the differences be- tween the generated visual attention and human- ... See full document
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Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding
... or visual information with vector representations trained from large lan- guage or visual datasets has been successfully explored in recent ...as visual question answering require ... See full document
12
Character Level Question Answering with Attention
... character-level, attention-based encoder-decoder model for question ...the attention distribution reveal that our model, although built on character-level inputs, can learn ... See full document
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KVQA: Knowledge-Aware Visual Question Answering
... Question answering about image, also popularly known as Visual Question Answering (VQA), has gained huge inter- est in recent years (Goyal et ...scale Visual Question ... See full document
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Analyzing the Behavior of Visual Question Answering Models
... the question (using Long Short-Term Memory (LSTM) recurrent neural network to obtain question ...and question features obtained from the two channels are combined and passed through a fully connected ... See full document
6
Stacking with Auxiliary Features for Visual Question Answering
... extracting visual explanations from several com- ponent models for each IQ pair and using those to also generate auxiliary features; and (c) us- ing SWAF to ensemble various VQA models and evaluating ablations of ... See full document
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Faithful Multimodal Explanation for Visual Question Answering
... both visual and multimodal ...of attention values and source identifiers’ values in Eq, 2 over time (t) and assign the accumulated attention weight to each corresponding segmenta- tion ...normalize ... See full document
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The Meaning of “Most” for Visual Question Answering Models
... a visual scene requires non-trivial inference ...for visual question answering learn when trained on such ques- ...same question was investigated for humans. Focusing on the FiLM ... See full document
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YNUDLG at IJCNLP 2017 Task 5: A CNN LSTM Model with Attention for Multi choice Question Answering in Examinations
... of question word embeddings to represent questions, which ignores word order information and cannot process complicated ...between question and answer. Question and answer vectors are put into a ... See full document
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Question Answering Using Hierarchical Attention on Top of BERT Features
... self-alignment attention in addressing the long- distance dependence was taken from (Wang et ...the question-aware passage representation with the passage self-aware ... See full document
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