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Visual Dialog
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Visual Dialog requires an AI agent to hold a meaningful dialog with humans in natural, conversational language about visual content. Specifically, given an image, a dialog history, and a follow-up question about the image, the task is to answer the question.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
SeqDialN: Sequential Visual Dialog Networks in Joint Visual-Linguistic Representation Space
Dialog without Dialog Data: Learning Visual Dialog Agents from VQA Data
ORD: Object Relationship Discovery for Visual Dialogue Generation
History for Visual Dialog: Do we really need it?
Multi-View Attention Network for Visual Dialog
VD-BERT: A Unified Vision and Dialog Transformer with BERT
Reasoning Visual Dialog with Sparse Graph Learning and Knowledge Transfer
Iterative Context-Aware Graph Inference for Visual Dialog
Modality-Balanced Models for Visual Dialogue
Ensemble based discriminative models for Visual Dialog Challenge 2018
Vision and Language: from Visual Perception to Content Creation
DMRM: A Dual-channel Multi-hop Reasoning Model for Visual Dialog
Large-scale Pretraining for Visual Dialog: A Simple State-of-the-Art Baseline
Efficient Attention Mechanism for Visual Dialog that can Handle All the Interactions between Multiple Inputs
Two Causal Principles for Improving Visual Dialog
An Annotated Corpus of Reference Resolution for Interpreting Common Grounding
DualVD: An Adaptive Dual Encoding Model for Deep Visual Understanding in Visual Dialogue
Visual Dialogue State Tracking for Question Generation
TAB-VCR: Tags and Attributes based Visual Commonsense Reasoning Baselines
Granular Multimodal Attention Networks for Visual Dialog
Improving Generative Visual Dialog by Answering Diverse Questions
On Controlled DeEntanglement for Natural Language Processing
Probabilistic framework for solving Visual Dialog
Building Task-Oriented Visual Dialog Systems Through Alternative Optimization Between Dialog Policy and Language Generation
Grounded Agreement Games: Emphasizing Conversational Grounding in Visual Dialogue Settings
Reactive Multi-Stage Feature Fusion for Multimodal Dialogue Modeling
What Should I Ask? Using Conversationally Informative Rewards for Goal-Oriented Visual Dialog
Learning Goal-Oriented Visual Dialog Agents: Imitating and Surpassing Analytic Experts
Reasoning Visual Dialogs with Structural and Partial Observations
Factor Graph Attention
CLEVR-Dialog: A Diagnostic Dataset for Multi-Round Reasoning in Visual Dialog
Discourse Parsing in Videos: A Multi-modal Appraoch
Image-Question-Answer Synergistic Network for Visual Dialog
Generative Visual Dialogue System via Adaptive Reasoning and Weighted Likelihood Estimation
Making History Matter: History-Advantage Sequence Training for Visual Dialog
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