Papers Visual Dialog
“Visual Dialog” 태그가 달린 논문 120편 · 필터 해제
Learning Goal-Oriented Visual Dialog Agents: Imitating and Surpassing Analytic Experts
This paper tackles the problem of learning a questioner in the goal-oriented visual dialog task. Several previous works adopt model-free reinforcement learning. Most pretrain the model from a finite set of human-generate…
Imitation Learningreinforcement-learningReinforcement LearningReinforcement Learning (RL)+1What Should I Ask? Using Conversationally Informative Rewards for Goal-oriented Visual Dialog.
The ability to engage in goal-oriented conversations has allowed humans to gain knowledge, reduce uncertainty, and perform tasks more efficiently. Artificial agents, however, are still far behind humans in having goal-dr…
Reinforcement LearningVisual DialogA Generative Adversarial Density Estimator
Density estimation is a challenging unsupervised learning problem. Current maximum likelihood approaches for density estimation are either restrictive or incapable of producing high-quality samples. On the other hand, li…
Density EstimationVisual DialogThe World in My Mind: Visual Dialog with Adversarial Multi-modal Feature Encoding
Visual Dialog is a multi-modal task that requires a model to participate in a multi-turn human dialog grounded on an image, and generate correct, human-like responses. In this paper, we propose a novel Adversarial Multi-…
General KnowledgeVisual DialogFactor Graph Attention
Dialog is an effective way to exchange information, but subtle details and nuances are extremely important. While significant progress has paved a path to address visual dialog with algorithms, details and nuances remain…
Graph AttentionQuestion AnsweringVisual DialogVisual Question Answering+1Reasoning Visual Dialogs with Structural and Partial Observations
We propose a novel model to address the task of Visual Dialog which exhibits complex dialog structures. To obtain a reasonable answer based on the current question and the dialog history, the underlying semantic dependen…
Graph Neural NetworkVisual DialogCLEVR-Dialog: A Diagnostic Dataset for Multi-Round Reasoning in Visual Dialog
Visual Dialog is a multimodal task of answering a sequence of questions grounded in an image, using the conversation history as context. It entails challenges in vision, language, reasoning, and grounding. However, study…
coreference-resolutionCoreference ResolutionDiagnosticVisual DialogDiscourse Parsing in Videos: A Multi-modal Appraoch
Text-level discourse parsing aims to unmask how two sentences in the text are related to each other. We propose the task of Visual Discourse Parsing, which requires understanding discourse relations among scenes in a vid…
Discourse ParsingVisual DialogVisual StorytellingImage-Question-Answer Synergistic Network for Visual Dialog
The image, question (combined with the history for de-referencing), and the corresponding answer are three vital components of visual dialog. Classical visual dialog systems integrate the image, question, and history to …
Visual DialogGenerative Visual Dialogue System via Adaptive Reasoning and Weighted Likelihood Estimation
The key challenge of generative Visual Dialogue (VD) systems is to respond to human queries with informative answers in natural and contiguous conversation flow. Traditional Maximum Likelihood Estimation (MLE)-based meth…
Visual DialogDual Attention Networks for Visual Reference Resolution in Visual Dialog
Visual dialog (VisDial) is a task which requires an AI agent to answer a series of questions grounded in an image. Unlike in visual question answering (VQA), the series of questions should be able to capture a temporal c…
AI AgentQuestion AnsweringVisual DialogVisual Grounding+2Making History Matter: History-Advantage Sequence Training for Visual Dialog
We study the multi-round response generation in visual dialog, where a response is generated according to a visually grounded conversational history. Given a triplet: an image, Q&A history, and current question, all the …
Answer GenerationDecoderReinforcement LearningResponse Generation+3Large-Scale Answerer in Questioner's Mind for Visual Dialog Question Generation
Answerer in Questioner's Mind (AQM) is an information-theoretic framework that has been recently proposed for task-oriented dialog systems. AQM benefits from asking a question that would maximize the information gain whe…
Question GenerationQuestion-GenerationVisual DialogMulti-step Reasoning via Recurrent Dual Attention for Visual Dialog
This paper presents a new model for visual dialog, Recurrent Dual Attention Network (ReDAN), using multi-step reasoning to answer a series of questions about an image. In each question-answering turn of a dialog, ReDAN i…
Question AnsweringVisual DialogResponse to "Visual Dialogue without Vision or Dialogue" (Massiceti et al., 2018)
In a recent workshop paper, Massiceti et al. presented a baseline model and subsequent critique of Visual Dialog (Das et al., CVPR 2017) that raises what we believe to be unfounded concerns about the dataset and evaluati…
Visual DialogVisual Dialogue without Vision or Dialogue
We characterise some of the quirks and shortcomings in the exploration of Visual Dialogue - a sequential question-answering task where the questions and corresponding answers are related through given visual stimuli. To …
Question AnsweringVisual DialogWhat's to know? Uncertainty as a Guide to Asking Goal-oriented Questions
One of the core challenges in Visual Dialogue problems is asking the question that will provide the most useful information towards achieving the required objective. Encouraging an agent to ask the right questions is dif…
Visual DialogGold Seeker: Information Gain from Policy Distributions for Goal-oriented Vision-and-Langauge Reasoning
As Computer Vision moves from a passive analysis of pixels to active analysis of semantics, the breadth of information algorithms need to reason over has expanded significantly. One of the key challenges in this vein is …
Reinforcement LearningVisual DialogPIRC Net : Using Proposal Indexing, Relationships and Context for Phrase Grounding
Phrase Grounding aims to detect and localize objects in images that are referred to and are queried by natural language phrases. Phrase grounding finds applications in tasks such as Visual Dialog, Visual Search and Image…
Phrase GroundingSentenceTransfer LearningVisual DialogRecursive Visual Attention in Visual Dialog
Visual dialog is a challenging vision-language task, which requires the agent to answer multi-round questions about an image. It typically needs to address two major problems: (1) How to answer visually-grounded question…
Question AnsweringVisual DialogVisual Question AnsweringVisual Question Answering (VQA)