boththequestionsandanswersareopen-ended.Visualques- tionsselectivelytargetdifferentareasofanimage,including backgrounddetailsandunderlyingcontext.Asaresult,asys- temthatsucceedsatVQAtypicallyneedsamoredetailed
Visual Question Answering is a semantic task that aims to answer questions based on an image. Source: [visualqa.org](https://visualqa.org/) 相关学科: Image CaptioningVisual ReasoningVisual DialogVisual GroundingRelational ReasoningQuestion AnsweringVisual Commonsense ReasoningReferring Expression ...
Since it requires a deep semantic and linguistic understanding of the question and the ability to associate it with various objects that are present in the image, it is an ambitious task and requires multi-modal reasoning from both computer vision and natural language processing. We propose ...
Human reasoners (without any special training) can provide sensible answers to such questions as early as age four, revealing deep understanding of spatial relations across different object categories1. How such abstraction is possible has been the focus of decades of research in cognitive science, ...
All 3 datasets are annotated with the corresponding correct answers, as shown in Table 1. The question categories are classified as judgment (yes/no), counting (number), and other questions; the accuracy is assessed independently during model evaluation. It remains a challenge to achieve high ...
For free-form, open-ended questions, the joint feature representations are converted into answers usually using a recurrent network like LSTMs.Wu et al. (2016)extract data about the image to provide the language model with more context. They use the Doc2Vec algorithm to get embeddings, which...
Lau JJ, Gayen S, Ben Abacha A, Demner-Fushman D (2018) A dataset of clinically generated visual questions and answers about radiology images. Scient Data 5(1):1–10 Article Google Scholar Zhan L-M, Liu B, Fan L, Chen J, Wu X-M (2020) Medical visual question answering via condit...
Visual Programming: Compositional visual reasoning without training Tanmay Gupta, Aniruddha Kembhavi PRIOR @ Allen Institute for AI https://prior.allenai.org/projects/visprog Visual Programming Visual Prediction Rationale Compositional Visual Question Answering IMAGE: Question: Ar...
questions, such as questions asking about objects that do not appear in the image. To address this issue, we propose CLIP-UP: CLIP-based Unanswerable Problem detection, a novel lightweight method for equipping VLMs with the ability to withhold answers to unanswerable questions. By leveraging ...
In this paper, we present an explicit reasoning layer on top of a set of penultimate neural network based systems. The reasoning layer enables reasoning and answering questions where additional knowledge is required, and at the same time provides an interpretable interface to the end users. ...