| _ | question | _ |
|---|
| 3DVQA: Visual | question | Answering for 3D Environments |
| 5 | question | s for Andrew Leland: The History of Assistive Technology for the Blind |
| 5 | question | s for Missy Cummings: The Former Fighter Pilot on why Autonomous Vehicles are so Risky |
| A-OKVQA: A Benchmark for Visual | question | Answering Using World Knowledge |
| A2A: Attention to Attention Reasoning for Movie | question | Answering |
| Accuracy vs. complexity: A trade-off in visual | question | answering models |
| Action-Centric Relation Transformer Network for Video | question | Answering |
| Adapting Grounded Visual | question | Answering Models to Low Resource Languages |
| ADCCF: Adaptive deep concatenation coder framework for visual | question | answering |
| Adversarial Multimodal Network for Movie Story | question | Answering |
| ALSA: Adversarial Learning of Supervised Attentions for Visual | question | Answering |
| Analysis of Visual | question | Answering Algorithms, An |
| Analyzing Geographic | question | s Using Embedding-based Topic Modeling |
| Anomaly Matters: An Anomaly-Oriented Model for Medical Visual | question | Answering |
| Answer Distillation for Visual | question | Answering |
| Answer Selection in Community | question | Answering via Attentive Neural Networks |
| Answer Them All! Toward Universal Visual | question | Answering Models |
| Answer-checking in Context: A Multi-modal Fully Attention Network for Visual | question | Answering |
| Answer-Type Prediction for Visual | question | Answering |
| Answering knowledge-based visual | question | s via the exploration of Question Purpose |
| Answering knowledge-based visual | question | s via the exploration of Question Purpose |
| Answering | question | s about Data Visualizations using Efficient Bimodal Fusion |
| Answering Visual What-If | question | s: From Actions to Predicted Scene Descriptions |
| Are we Asking the Right | question | s in MovieQA? |
| Are You Smarter Than a Sixth Grader? Textbook | question | Answering for Multimodal Machine Comprehension |
| Ask Me Anything: Free-Form Visual | question | Answering Based on Knowledge from External Sources |
| Ask Your Neurons: A Deep Learning Approach to Visual | question | Answering |
| Ask Your Neurons: A Neural-Based Approach to Answering | question | s about Images |
| Ask, Attend and Answer: Exploring | question | -Guided Spatial Attention for Visual Question Answering |
| Ask, Attend and Answer: Exploring | question | -Guided Spatial Attention for Visual Question Answering |
| AssistQ: Affordance-Centric | question | -Driven Task Completion for Egocentric Assistant |
| Auto QA: The | question | Is Not Only What, but Also Where |
| Auto-Parsing Network for Image Captioning and Visual | question | Answering |
| Automatic | question | Tagging using k-Nearest Neighbors and Random Forest |
| Barlow constrained optimization for Visual | question | Answering |
| BERT Representations for Video | question | Answering |
| Better Way to Attend: Attention With Trees for Video | question | Answering, A |
| Beyond | question | -Based Biases: Assessing Multimodal Shortcut Learning in Visual Question Answering |
| Beyond | question | -Based Biases: Assessing Multimodal Shortcut Learning in Visual Question Answering |
| Beyond VQA: Generating Multi-word Answers and Rationales to Visual | question | s |
| Bilaterally Slimmable Transformer for Elastic and Efficient Visual | question | Answering |
| Biometric surveillance using visual | question | answering |
| Bottom-Up and Top-Down Attention for Image Captioning and Visual | question | Answering |
| Bridge to Answer: Structure-aware Graph Interaction Network for Video | question | Answering |
| Bridging Video-Text Retrieval with Multiple Choice | question | s |
| CAAN: Context-Aware attention network for visual | question | answering |
| Cascade transformers with dynamic attention for video | question | answering |
| cascaded long short-term memory (LSTM) driven generic visual | question | answering (VQA), A |
| CAT: Re-Conv Attention in Transformer for Visual | question | Answering |
| CLIP-Guided Vision-Language Pre-training for | question | Answering in 3D Scenes |
| Coarse to Fine Frame Selection for Online Open-ended Video | question | Answering |
| Coarse-to-Fine Reasoning for Visual | question | Answering |
| Coarse-to-Fine Visual | question | Answering by Iterative, Conditional Refinement |
| Colour and Space in Cultural Heritage: Key | question | s in 3D Optical Documentation of Material Culture for Conservation, Study and Preservation |
| Combining Multiple Cues for Visual Madlibs | question | Answering |
| Compact Trilinear Interaction for Visual | question | Answering |
| Competence-aware Curriculum for Visual Concepts Learning via | question | Answering, A |
| Compositional Attention Networks With Two-Stream Fusion for Video | question | Answering |
| Comprehensive-perception dynamic reasoning for visual | question | answering |
| Context Relation Fusion Model for Visual | question | Answering |
| Context-VQA: Towards Context-Aware and Purposeful Visual | question | Answering |
| Contrastive Video | question | Answering via Video Graph Transformer |
| Correlation Information Bottleneck: Towards Adapting Pretrained Multimodal Models for Robust Visual | question | Answering |
| Counterfactual Samples Synthesizing and Training for Robust Visual | question | Answering |
| Counterfactual Samples Synthesizing for Robust Visual | question | Answering |
| Counting-based visual | question | answering with serial cascaded attention deep learning |
| Creativity: Generating Diverse | question | s Using Variational Autoencoders |
| Cross-Attentional Spatio-Temporal Semantic Graph Networks for Video | question | Answering |
| Cross-Dataset Adaptation for Visual | question | Answering |
| Cross-Modal Causal Relational Reasoning for Event-Level Visual | question | Answering |
| Cross-Modal Dense Passage Retrieval for Outside Knowledge Visual | question | Answering |
| Cross-modal knowledge reasoning for knowledge-based visual | question | answering |
| Cross-modal Relational Reasoning Network for Visual | question | Answering |
| Cross-Modal Visual | question | Answering for Remote Sensing Data: the International Conference on Digital Image Computing: Techniques and Applications (DICTA 2021) |
| CS-VQA: Visual | question | Answering with Compressively Sensed Images |
| Customized Image Narrative Generation via Interactive Visual | question | Generation and Answering |
| Cycle-Consistency for Robust Visual | question | Answering |
| DAPC: Answering Why-Not | question | s on Top-k Direction-Aware ASK Queries in Polar Coordinates |
| Dataset and Exploration of Models for Understanding Video Data through Fill-in-the-Blank | question | -Answering, A |
| Dealing with Missing Modalities in the Visual | question | Answer-Difference Prediction Task through Knowledge Distillation |
| Debiased Visual | question | Answering via the perspective of question types |
| Debiased Visual | question | Answering via the perspective of question types |
| DecomVQANet: Decomposing visual | question | answering deep network via tensor decomposition and regression |
| Decouple Before Interact: Multi-Modal Prompt Learning for Continual Visual | question | Answering |
| Deep Attention Neural Tensor Network for Visual | question | Answering |
| Deep Bayesian Network for Visual | question | Generation |
| Deep Modular Co-Attention Networks for Visual | question | Answering |
| Deep Residual Weight-Sharing Attention Network With Low-Rank Attention for Visual | question | Answering |
| Depth and Video Segmentation Based Visual Attention for Embodied | question | Answering |
| Depth-Aware and Semantic Guided Relational Attention Network for Visual | question | Answering |
| Diagnostic Study of Visual | question | Answering With Analogical Reasoning, A |
| Differential Attention for Visual | question | Answering |
| DisAVR: Disentangled Adaptive Visual Reasoning Network for Diagram | question | Answering |
| Discovering Spatio-Temporal Rationales for Video | question | Answering |
| Discovering the Real Association: Multimodal Causal Reasoning in Video | question | Answering |
| Divide and Conquer: Answering | question | s with Object Factorization and Compositional Reasoning |
| Document Image Retrieval in a | question | Answering System for Document Images |
| Does ChatGPT Spell the End of Automatic | question | Generation Research? |
| Does the Research | question | Structure Impact the Attention Model? User Study Experiment |
| Don't Just Assume; Look and Answer: Overcoming Priors for Visual | question | Answering |
| DRAU: Dual Recurrent Attention Units for Visual | question | Answering |
| DSGEM: Dual scene graph enhancement module-based visual | question | answering |
| Dual Path Multi-Modal High-Order Features for Textual Content based Visual | question | Answering |
| Dual self-attention with co-attention networks for visual | question | answering |
| Dual-Attention Learning Network With Word and Sentence Embedding for Medical Visual | question | Answering, A |
| Dual-decoder transformer network for answer grounding in visual | question | answering |
| Dual-Key Multimodal Backdoors for Visual | question | Answering |
| DualVGR: A Dual-Visual Graph Reasoning Unit for Video | question | Answering |
| DVQA: Understanding Data Visualizations via | question | Answering |
| Dynamic dual graph networks for textbook | question | answering |
| Dynamic Fusion With Intra- and Inter-Modality Attention Flow for Visual | question | Answering |
| Dynamic Self-Attention with Vision Synchronization Networks for Video | question | Answering |
| DynGraph: Visual | question | Answering via Dynamic Scene Graphs |
| Editorial paper for Pattern Recognition Letters VSI on Cross Model Understanding for Visual | question | Answering |
| Editorial to special issue on cross-media learning for visual | question | answering |
| Efficient Counterfactual Debiasing for Visual | question | Answering |
| EgoVQA: An Egocentric Video | question | Answering Benchmark Dataset |
| Embedding Spatial Relations in Visual | question | Answering for Remote Sensing |
| Embodied | question | Answering |
| Embodied | question | Answering |
| Embodied | question | Answering in Photorealistic Environments With Point Cloud Perception |
| Empirical Evaluation of Visual | question | Answering for Novel Objects, An |
| Empirical study on using adapters for debiased Visual | question | Answering |
| Encoder-decoder cycle for visual | question | answering based on perception-action cycle |
| Encyclopedic VQA: Visual | question | s about detailed properties of fine-grained categories |
| End-to-End Concept Word Detection for Video Captioning, Retrieval, and | question | Answering |
| End-to-End Video | question | -Answer Generation With Generator-Pretester Network |
| Env-QA: A Video | question | Answering Benchmark for Comprehensive Understanding of Dynamic Environments |
| Episodic Memory | question | Answering |
| ERM: Energy-Based Refined-Attention Mechanism for Video | question | Answering |
| Estimation Of Visual Contents Based On | question | Answering From Human Brain Activity |
| Evaluation of a Visual | question | Answering Architecture for Pedestrian Attribute Recognition |
| Event Graph Guided Compositional Spatial-Temporal Reasoning for Video | question | Answering |
| Existence | question | for Maximum-Likelihood Estimators in Time-of-Arrival-Based Localization, The |
| Explicit Bias Discovery in Visual | question | Answering Models |
| Explicit ensemble attention learning for improving visual | question | answering |
| External Commonsense Knowledge as a Modality for Social Intelligence | question | -Answering |
| Face-to-Face Contrastive Learning for Social Intelligence | question | -Answering |
| Facial expression of emotion: New findings, new | question | s |
| Fantastic Answers and Where to Find Them: Immersive | question | -Directed Visual Attention |
| FashionVQA: A Domain-Specific Visual | question | Answering System |
| Focal Visual-Text Attention for Memex | question | Answering |
| Focal Visual-Text Attention for Visual | question | Answering |
| Found a Reason for me? Weakly-supervised Grounded Visual | question | Answering using Capsules |
| Four National Maps of Broad Forest Type Provide Inconsistent Answers to the | question | of What Burns in Canada |
| Frame Augmented Alternating Attention Network for Video | question | Answering |
| Frequently Asked/Answered | question | |
| From Images to Textual Prompts: Zero-shot Visual | question | Answering with Frozen Large Language Models |
| From known to the unknown: Transferring knowledge to answer | question | s about novel visual and semantic concepts |
| From Representation to Reasoning: Towards both Evidence and Commonsense Reasoning for Video | question | -Answering |
| GDUMB: A Simple Approach that | question | s Our Progress in Continual Learning |
| Generalized Hadamard-Product Fusion Operators for Visual | question | Answering |
| Generalized pyramid co-attention with learnable aggregation net for video | question | answering |
| Generative Bias for Robust Visual | question | Answering |
| Geographic Knowledge Base | question | Answering over OpenStreetMap |
| Goal-Oriented Visual | question | Generation via Intermediate Rewards |
| Good, Better, Best: Textual Distractors Generation for Multiple-Choice Visual | question | Answering via Reinforcement Learning |
| GQA: A New Dataset for Real-World Visual Reasoning and Compositional | question | Answering |
| Grad-Cam Aware Supervised Attention for Visual | question | Answering for Post-Disaster Damage Assessment |
| Graph-Based Multi-Interaction Network for Video | question | Answering |
| Graph-Structured Representations for Visual | question | Answering |
| Greedy Gradient Ensemble for Robust Visual | question | Answering |
| Grounding Answers for Visual | question | s Asked by Visually Impaired People |
| Guiding Visual | question | Answering with Attention Priors |
| HAIR: Hierarchical Visual-Semantic Relational Reasoning for Video | question | Answering |
| Health-Oriented Multimodal Food | question | Answering |
| Heterogeneous Community | question | Answering via Social-Aware Multi-Modal Co-Attention Convolutional Matching |
| Heterogeneous Memory Enhanced Multimodal Attention Model for Video | question | Answering |
| Hierarchical Conditional Relation Networks for Multimodal Video | question | Answering |
| Hierarchical Conditional Relation Networks for Video | question | Answering |
| Hierarchical Relational Attention for Video | question | Answering |
| Hierarchical Representation Network With Auxiliary Tasks for Video Captioning and Video | question | Answering |
| Holistic Multi-Modal Memory Network for Movie | question | Answering |
| Human Attention in Visual | question | Answering: Do Humans and Deep Networks Look at the Same Regions? |
| Image Captioning and Visual | question | Answering Based on Attributes and External Knowledge |
| Image Quality Evaluation in Professional HDR/WCG Production | question | s the Need for HDR Metrics |
| Image | question | Answering Using Convolutional Neural Network with Dynamic Parameter Prediction |
| Image segmentation in Twenty | question | s |
| Image- | question | -Answer Synergistic Network for Visual Dialog |
| Improved Attention for Visual | question | Answering, An |
| Improved Fusion of Visual and Language Representations by Dense Symmetric Co-attention for Visual | question | Answering |
| Improving Selective Visual | question | Answering by Learning from Your Peers |
| Improving Visual | question | Answering using Active Perception on Static Images |
| Improving visual | question | answering using dropout and enhanced question encoder |
| Improving visual | question | answering using dropout and enhanced question encoder |
| In Defense of Grid Features for Visual | question | Answering |
| Incorporating 3D Information Into Visual | question | Answering |
| Information Maximizing Visual | question | Generation |
| Interpretable Visual | question | Answering by Reasoning on Dependency Trees |
| Interpretable Visual | question | Answering by Visual Grounding From Attention Supervision Mining |
| Interpretable Visual | question | Answering Referring to Outside Knowledge |
| Interpretable Visual | question | Answering Via Reasoning Supervision |
| Invariant Grounding for Video | question | Answering |
| Inverse Visual | question | Answering: A New Benchmark and VQA Diagnosis Tool |
| IQ-VQA: Intelligent Visual | question | Answering |
| IQA: Visual | question | Answering in Interactive Environments |
| Is GPT-3 All You Need for Visual | question | Answering in Cultural Heritage? |
| ISD-QA: Iterative Distillation of Commonsense Knowledge from General Language Models for Unsupervised | question | Answering |
| It's Not About the Journey; It's About the Destination: Following Soft Paths Under | question | -Guidance for Visual Reasoning |
| iVQA: Inverse Visual | question | Answering |
| Joint Sequence Fusion Model for Video | question | Answering and Retrieval, A |
| Just Ask: Learning to Answer | question | s from Millions of Narrated Videos |
| K-VQG: Knowledge-aware Visual | question | Generation for Common-sense Acquisition |
| Keyword-Aware Relative Spatio-Temporal Graph Networks for Video | question | Answering |
| Knowing Where to Look? Analysis on Attention of Visual | question | Answering System |
| Knowledge Acquisition for Visual | question | Answering via Iterative Querying |
| Knowledge base graph embedding module design for Visual | question | answering model |
| Knowledge Proxy Intervention for Deconfounded Video | question | Answering |
| Knowledge-Augmented Visual | question | Answering With Natural Language Explanation |
| Knowledge-Based Embodied | question | Answering |
| Knowledge-based Video | question | Answering with Unsupervised Scene Descriptions |
| Knowledge-Based Visual | question | Generation |
| Language and Visual Relations Encoding for Visual | question | Answering |
| Language Models are Causal Knowledge Extractors for Zero-shot Video | question | Answering |
| Latent Variable Models for Visual | question | Answering |
| LEAF-QA: Locate, Encode Attend for Figure | question | Answering |
| Learning Answer Embeddings for Visual | question | Answering |
| Learning by Asking | question | s |
| Learning Models for Actions and Person-Object Interactions with Transfer to | question | Answering |
| Learning Situation Hyper-Graphs for Video | question | Answering |
| Learning to Answer | question | s in Dynamic Audio-Visual Scenarios |
| Learning to Ask Informative Sub- | question | s for Visual Question Answering |
| Learning to Ask Informative Sub- | question | s for Visual Question Answering |
| Learning to Caption Images Through a Lifetime by Asking | question | s |
| Learning to Disambiguate by Asking Discriminative | question | s |
| Learning to Reason: End-to-End Module Networks for Visual | question | Answering |
| Learning to Supervise Knowledge Retrieval Over a Tree Structure for Visual | question | Answering |
| Learning Visual Knowledge Memory Networks for Visual | question | Answering |
| Learning Visual | question | Answering by Bootstrapping Hard Attention |
| Learning visual | question | answering on controlled semantic noisy labels |
| Leveraging | question | Answering for Domain-Agnostic Information Extraction |
| Leveraging Visual | question | Answering for Image-Caption Ranking |
| Linguistically Routing Capsule Network for Out-of-distribution Visual | question | Answering |
| LiVLR: A Lightweight Visual-Linguistic Reasoning Framework for Video | question | Answering |
| LLQA: Lifelog | question | Answering Dataset |
| Local relation network with multilevel attention for visual | question | answering |
| Locate Before Answering: Answer Guided | question | Localization for Video Question Answering |
| Locate Before Answering: Answer Guided | question | Localization for Video Question Answering |
| Locating Visual Explanations for Video | question | Answering |
| Logical Implications for Visual | question | Answering Consistency |
| LOIS: Looking Out of Instance Semantics for Visual | question | Answering |
| Long video | question | answering: A Matching-guided Attention Model |
| Long-Form Video | question | Answering via Dynamic Hierarchical Reinforced Networks |
| Long-Term Video | question | Answering via Multimodal Hierarchical Memory Attentive Networks |
| Machine Learning Based Methods for Arabic Duplicate | question | Detection |
| Maintaining Reasoning Consistency in Compositional Visual | question | Answering |
| Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual | question | Answering |
| MarioQA: Answering | question | s by Watching Gameplay Videos |
| Markov Network Based Passage Retrieval Method for Multimodal | question | Answering in the Cultural Heritage Domain, A |
| Measuring Compositional Consistency for Video | question | Answering |
| Medical Visual | question | Answering via Conditional Reasoning and Contrastive Learning |
| Mining deep And-Or object structures via cost-sensitive | question | -answer-based active annotations |
| Mining Interpretable AOG Representations From Convolutional Networks via Active | question | Answering |
| Mining Object Parts from CNNs via Active | question | -Answering |
| MIST: Multi-modal Iterative Spatial-Temporal Transformer for Long-form Video | question | Answering |
| MixPHM: Redundancy-Aware Parameter-Efficient Tuning for Low-Resource Visual | question | Answering |
| MMTF: Multi-Modal Temporal Fusion for Commonsense Video | question | Answering |
| MoCA: Incorporating domain pretraining and cross attention for textbook | question | answering |
| Modality Shifting Attention Network for Multi-Modal Video | question | Answering |
| MoQA: A Multi-modal | question | Answering Architecture |
| Motion-Appearance Co-memory Networks for Video | question | Answering |
| Movie | question | Answering via Textual Memory and Plot Graph |
| MovieQA: Understanding Stories in Movies through | question | -Answering |
| MuKEA: Multimodal Knowledge Extraction and Accumulation for Knowledge-based Visual | question | Answering |
| Multi-agent Embodied | question | Answering in Interactive Environments |
| Multi-Granularity Interaction and Integration Network for Video | question | Answering |
| Multi-level Attention Networks for Visual | question | Answering |
| Multi-modal Contextual Graph Neural Network for Text Visual | question | Answering |
| Multi-Modal Correlated Network with Emotional Reasoning Knowledge for Social Intelligence | question | -Answering |
| Multi-modal Factorized Bilinear Pooling with Co-attention Learning for Visual | question | Answering |
| Multi-modal spatial relational attention networks for visual | question | answering |
| Multi-Modality Latent Interaction Network for Visual | question | Answering |
| Multi-scale relation reasoning for multi-modal Visual | question | Answering |
| Multi-scale Relational Reasoning with Regional Attention for Visual | question | Answering |
| Multi-Semantic Alignment Co-Reasoning Network for Video | question | Answering |
| Multi-stage Attention based Visual | question | Answering |
| Multi-Target Embodied | question | Answering |
| Multi-Tier Attention Network using Term-weighted | question | Features for Visual Question Answering |
| Multi-Tier Attention Network using Term-weighted | question | Features for Visual Question Answering |
| Multi-Turn Video | question | Answering via Hierarchical Attention Context Reinforced Networks |
| Multi-Turn Video | question | Generation via Reinforced Multi-Choice Attention Network |
| Multimodal Dual Attention Memory for Video Story | question | Answering |
| Multimodal grid features and cell pointers for scene text visual | question | answering |
| Multimodal Integration of Human-Like Attention in Visual | question | Answering |
| Multitask learning for neural generative | question | answering |
| Multiview Language Bias Reduction for Visual | question | Answering |
| MUREL: Multimodal Relational Reasoning for Visual | question | Answering |
| MUTAN: Multimodal Tucker Fusion for Visual | question | Answering |
| NAAQA: A Neural Architecture for Acoustic | question | Answering |
| Natural Language Video Localization: A Revisit in Span-Based | question | Answering Framework |
| New Passage Ranking Algorithm for Video | question | Answering, A |
| NExT-QA: Next Phase of | question | -Answering to Explaining Temporal Actions |
| novel feature extractor for human action recognition in visual | question | answering, A |
| NRTK, PPP or Static, That Is the | question | . Testing Different Positioning Solutions for GNSS Survey |
| Object detection in 20 | question | s |
| Object sequences: encoding categorical and spatial information for a yes/no visual | question | answering task |
| OK-VQA: A Visual | question | Answering Benchmark Requiring External Knowledge |
| On the General Value of Evidence, and Bilingual Scene-Text Visual | question | Answering |
| On the hidden treasure of dialog in video | question | answering |
| On the role of | question | encoder sequence model in robust visual question answering |
| On the role of | question | encoder sequence model in robust visual question answering |
| Ontology-Driven Cyberinfrastructure for Intelligent Spatiotemporal | question | Answering and Open Knowledge Discovery, An |
| Open-Ended Video | question | Answering via Multi-Modal Conditional Adversarial Networks |
| Open-Vocabulary Video | question | Answering: A New Benchmark for Evaluating the Generalizability of Video Question Answering Models |
| Open-Vocabulary Video | question | Answering: A New Benchmark for Evaluating the Generalizability of Video Question Answering Models |
| P ˜ NP, at least in Visual | question | Answering |
| Pano-AVQA: Grounded Audio-Visual | question | Answering on 360° Videos |
| Pattern-information fMRI: New | question | s which it opens up and challenges which face it |
| People Tracking in Camera Networks: Three Open | question | s |
| Plenty is Plague: Fine-Grained Learning for Visual | question | Answering |
| Positional Attention Guided Transformer-Like Architecture for Visual | question | Answering |
| PQA: Perceptual | question | Answering |
| Predicting Human Scanpaths in Visual | question | Answering |
| Predicting the quality of user-generated answers using co-training in community-based | question | answering portals |
| Prior Visual Relationship Reasoning For Visual | question | Answering |
| Progressive Attention Memory Network for Movie Story | question | Answering |
| Prompt-RSVQA: Prompting visual context to a language model for Remote Sensing Visual | question | Answering |
| Prompting Large Language Models with Answer Heuristics for Knowledge-Based Visual | question | Answering |
| QUALIFIER: | question | -Guided Self-Attentive Multimodal Fusion Network for Audio Visual Scene-Aware Dialog |
| Ques-to-Visual Guided Visual | question | Answering |
| question | Answering over Community-Contributed Web Videos |
| question | classification based on co-training style semi-supervised learning |
| question | Classification Based on Weak Supervision and Interrogative Pronouns Attention Mechanism |
| question | Classification for Intelligent Question Answering: A Comprehensive Survey |
| question | Classification for Intelligent Question Answering: A Comprehensive Survey |
| question | interface for 3D picture creation on an autostereoscopic digital picture frame |
| question | Type Guided Attention in Visual Question Answering |
| question | Type Guided Attention in Visual Question Answering |
| question | -Agnostic Attention for Visual Question Answering |
| question | -Agnostic Attention for Visual Question Answering |
| question | -aware dynamic scene graph of local semantic representation learning for visual question answering |
| question | -aware dynamic scene graph of local semantic representation learning for visual question answering |
| question | -Centric Model for Visual Question Answering in Medical Imaging, A |
| question | -Centric Model for Visual Question Answering in Medical Imaging, A |
| question | -Guided Hybrid Convolution for Visual Question Answering |
| question | -Guided Hybrid Convolution for Visual Question Answering |
| question | s of Uniqueness and Resolution in Reconstruction from Projections |
| Ranking answers of comparative | question | s using heterogeneous information organization from social media |
| Re-Attention for Visual | question | Answering |
| Reasoning on the Relation: Enhancing Visual Representation for Visual | question | Answering and Cross-Modal Retrieval |
| Recent Advances in Video | question | Answering: A Review of Datasets and Methods |
| Recovering Generalization via Pre-Training-Like Knowledge Distillation for Out-of-Distribution Visual | question | Answering |
| Reducing Language Biases in Visual | question | Answering with Visually-grounded Question Encoder |
| Reducing Language Biases in Visual | question | Answering with Visually-grounded Question Encoder |
| Relation-Aware Graph Attention Network for Visual | question | Answering |
| Relevance-aware | question | Generation in Non-task-oriented Dialogue Systems |
| Reliable Visual | question | Answering: Abstain Rather Than Answer Incorrectly |
| Rephrasing Visual | question | s by Specifying the Entropy of the Answer Distribution |
| Resolving Zero-Shot and Fact-Based Visual | question | Answering via Enhanced Fact Retrieval |
| Rethinking Data Augmentation for Robust Visual | question | Answering |
| Retrieving-to-Answer: Zero-Shot Video | question | Answering with Frozen Large Language Models |
| Revisiting Visual | question | Answering Baselines |
| RMLVQA: A Margin Loss Approach For Visual | question | Answering with Language Biases |
| Robust Explanations for Visual | question | Answering |
| robust multivariate reranking algorithm for | question | Answering enrichment, A |
| Robust Passage Retrieval Algorithm for Video | question | Answering, A |
| Robust visual | question | answering via semantic cross modal augmentation |
| RSVQA: Visual | question | Answering for Remote Sensing Data |
| RUArt: A Novel Text-Centered Solution for Text-Based Visual | question | Answering |
| ScanQA: 3D | question | Answering for Spatial Scene Understanding |
| Scene Graph Refinement Network for Visual | question | Answering |
| Scene Text Visual | question | Answering |
| Second Order Enhanced Multi-Glimpse Attention in Visual | question | Answering |
| See and Learn More: Dense Caption-Aware Representation for Visual | question | Answering |
| SegEQA: Video Segmentation Based Visual Attention for Embodied | question | Answering |
| Self-Adaptive Neural Module Transformer for Visual | question | Answering |
| SelfGraphVQA: A Self-Supervised Graph Neural Network for Scene-based | question | Answering |
| semantic approach for | question | classification using WordNet and Wikipedia, A |
| Semantic Equivalent Adversarial Data Augmentation for Visual | question | Answering |
| Semantic-Aware Modular Capsule Routing for Visual | question | Answering |
| Semantically Guided Visual | question | Answering |
| Separating Skills and Concepts for Novel Visual | question | Answering |
| Sim VQA: Exploring Simulated Environments for Visual | question | Answering |
| Simple and effective visual | question | answering in a single modality |
| Simple Baselines for Interactive Video Retrieval with | question | s and Answers |
| Simple contrastive learning in a self-supervised manner for robust visual | question | answering |
| So Many Heads, So Many Wits: Multimodal Graph Reasoning for Text-Based Visual | question | Answering |
| Social-IQ: A | question | Answering Benchmark for Artificial Social Intelligence |
| Spatial-Semantic Collaborative Graph Network for Textbook | question | Answering |
| Spatio-Temporal Two-stage Fusion for video | question | answering |
| SQuINTing at VQA Models: Introspecting VQA Models With Sub- | question | s |
| StableNet: Distinguishing the hard samples to overcome language priors in visual | question | answering |
| Stacked Attention Networks for Image | question | Answering |
| Straight to the Facts: Learning Knowledge Base Retrieval for Factual Visual | question | Answering |
| Structured Attentions for Visual | question | Answering |
| Structured Semantic Representation for Visual | question | Answering |
| Structured Triplet Learning with POS-Tag Guided Attention for Visual | question | Answering |
| survey of methods, datasets and evaluation metrics for visual | question | answering, A |
| SUTD-TrafficQA: A | question | Answering Benchmark and an Efficient Network for Video Reasoning over Traffic Events |
| SwapMix: Diagnosing and Regularizing the Over-Reliance on Visual Context in Visual | question | Answering |
| Task-Oriented Multi-Modal | question | Answering For Collaborative Applications |
| Tem-adapter: Adapting Image-Text Pretraining for Video | question | Answer |
| Temporal Moment Localization via Natural Language by Utilizing Video | question | Answers as a Special Variant and Bypassing NLP for Corpora |
| Ten Research | question | s for Scalable Multimedia Analytics |
| Term Weighting Schemes for | question | Categorization |
| Test-Time Model Adaptation for Visual | question | Answering With Debiased Self-Supervisions |
| Text-Guided Object Detector for Multi-modal Video | question | Answering |
| Text-instance graph: Exploring the relational semantics for text-based visual | question | answering |
| Textbook | question | Answering Under Instructor Guidance with Memory Networks |
| TGIF-QA: Toward Spatio-Temporal Reasoning in Visual | question | Answering |
| TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with | question | Answering |
| Time-aware Circulant Matrices for | question | -based Temporal Localization |
| Tips and Tricks for Visual | question | Answering: Learnings from the 2017 Challenge |
| To Complete or to Estimate, That is the | question | : A Multi-Task Approach to Depth Completion and Monocular Depth Estimation |
| To Filter Prune, or to Layer Prune, That Is the | question | |
| Toward Explainable 3D Grounded Visual | question | Answering: A New Benchmark and Strong Baseline |
| Toward Unsupervised Realistic Visual | question | Answering |
| Towards Unconstrained Pointing Problem of Visual | question | Answering: A Retrieval-based Method |
| Tracking Roads in Satellite Images by Playing Twenty | question | s |
| Transfer Learning via Unsupervised Task Discovery for Visual | question | Answering |
| Transform-Retrieve-Generate: Natural Language-Centric Outside-Knowledge Visual | question | Answering |
| Transformer-based Medical Visual | question | Answering Model, A |
| TRAR: Routing the Attention Spans in Transformer for Visual | question | Answering |
| Triple attention network for sentimental visual | question | answering |
| TRRNET: Tiered Relation Reasoning for Compositional Visual | question | Answering |
| Two Can Play This Game: Visual Dialog with Discriminative | question | Generation and Answering |
| Two-stage Multimodality Fusion for High-performance Text-based Visual | question | Answering |
| Two-Step Neural Network Approach to Passage Retrieval for Open Domain | question | Answering, A |
| Unbiased Visual | question | Answering by Leveraging Instrumental Variable |
| Uncovering the Temporal Context for Video | question | Answering |
| Understanding Knowledge Gaps in Visual | question | Answering: Implications for Gap Identification and Testing |
| Understanding Video Scenes through Text: Insights from Text-based Video | question | Answering |
| Unified | question | er Transformer for Descriptive Question Generation in Goal-Oriented Visual Dialogue |
| Unifying the Video and | question | Attentions for Open-Ended Video Question Answering |
| Unifying the Video and | question | Attentions for Open-Ended Video Question Answering |
| Unshuffling Data for Improved Generalization in Visual | question | Answering |
| V-Doc: Visual | question | s answers with Documents |
| Variational Causal Inference Network for Explanatory Visual | question | Answering |
| VC-VQA: Visual Calibration Mechanism For Visual | question | Answering |
| VIBIKNet: Visual Bidirectional Kernelized Network for Visual | question | Answering |
| Video Graph Transformer for Video | question | Answering |
| Video | question | Answering Using Clip-Guided Visual-Text Attention |
| Video | question | Answering Using Language-Guided Deep Compressed-Domain Video Feature |
| Video | question | Answering with Iterative Video-Text Co-tokenization |
| Video | question | Answering With Prior Knowledge and Object-Sensitive Learning |
| Video | question | Answering with Spatio-Temporal Reasoning |
| Video | question | Answering, Movies, Spatio-Temporal, Query, VQA |
| Vision and Text Transformer for Predicting Answerability on Visual | question | Answering |
| VisKE: Visual knowledge extraction and | question | answering by visual verification of relation phrases |
| Visual Madlibs: Fill in the Blank Description Generation and | question | Answering |
| Visual | question | Answering as a Meta Learning Task |
| Visual | question | Answering as Reading Comprehension |
| Visual | question | answering from another perspective: CLEVR mental rotation tests |
| Visual | question | answering in the medical domain based on deep learning approaches: A comprehensive study |
| Visual | question | answering model based on graph neural network and contextual attention |
| Visual | question | Answering Model Based on Visual Relationship Detection |
| Visual | question | Answering Network Merging High- and Low-Level Semantic Information, A |
| Visual | question | Answering on 360° Images |
| Visual | question | Answering on Image Sets |
| Visual | question | answering with attention transfer and a cross-modal gating mechanism |
| Visual | question | Answering With Dense Inter- and Intra-Modality Interactions |
| Visual | question | answering with gated relation-aware auxiliary |
| Visual | question | Answering with Memory-Augmented Networks |
| Visual | question | Answering with Textual Representations for Images |
| Visual | question | Answering, Datasets, Benchmarks, Surveys |
| Visual | question | Answering, Query, VQA |
| Visual | question | answering: A survey of methods and datasets |
| Visual | question | Answering: A Tutorial |
| Visual | question | answering: Datasets, algorithms, and future challenges |
| Visual | question | answering: Which investigated applications? |
| Visual | question | Generation as Dual Task of Visual Question Answering |
| Visual | question | Generation as Dual Task of Visual Question Answering |
| Visual | question | Generation for Class Acquisition of Unknown Objects |
| Visual | question | Generation Under Multi-granularity Cross-Modal Interaction |
| Visual | question | Generation: The State of the Art |
| Visual | question | Reasoning on General Dependency Tree |
| Visual-Textual Image Understanding and Retrieval - Joint Workshop on Content-Based Image Retrieval, Video and Image | question | Answering, Texture Analysis, Classification and Retrieval |
| Visual7W visual | question | answering |
| Visual7W: Grounded | question | Answering in Images |
| VizWiz Grand Challenge: Answering Visual | question | s from Blind People |
| VLC-BERT: Visual | question | Answering with Contextualized Commonsense Knowledge |
| VQA as a factoid | question | answering problem: A novel approach for knowledge-aware and explainable visual question answering |
| VQA as a factoid | question | answering problem: A novel approach for knowledge-aware and explainable visual question answering |
| VQA With No | question | s-Answers Training |
| VQA, Visual | question | Answering, Neural Networks |
| VQA-E: Explaining, Elaborating, and Enhancing Your Answers for Visual | question | s |
| VQA-GNN: Reasoning with Multimodal Knowledge via Graph Neural Networks for Visual | question | Answering |
| VQA-LOL: Visual | question | Answering Under the Lens of Logic |
| VQA-Machine: Learning How to Use Existing Vision Algorithms to Answer New | question | s, The |
| VQA: Visual | question | Answering |
| VQA: Visual | question | Answering |
| VQA: Visual | question | Answering |
| VQACL: A Novel Visual | question | Answering Continual Learning Setting |
| VQAMix: Conditional Triplet Mixup for Medical Visual | question | Answering |
| VQAPT: A New visual | question | answering model for personality traits in social media images |
| VQS: Linking Segmentations to | question | s and Answers for Supervised Attention in VQA and Question-Focused Semantic Segmentation |
| VQS: Linking Segmentations to | question | s and Answers for Supervised Attention in VQA and Question-Focused Semantic Segmentation |
| VQuAD: Video | question | Answering Diagnostic Dataset |
| Weakly Supervised Learning for Textbook | question | Answering |
| Weakly Supervised Relative Spatial Reasoning for Visual | question | Answering |
| Weakly Supervised Visual | question | Answer Generation |
| Weakly-Supervised 3D Spatial Reasoning for Text-Based Visual | question | Answering |
| What's in a | question | : Using Visual Questions as a Form of Supervision |
| What's in a | question | : Using Visual Questions as a Form of Supervision |
| What's to Know? Uncertainty as a Guide to Asking Goal-Oriented | question | s |
| Where did I leave my keys?: Episodic-Memory-Based | question | Answering on Egocentric Videos |
| Where to Look: Focus Regions for Visual | question | Answering |
| Why Does a Visual | question | Have Different Answers? |
| Yin and Yang: Balancing and Answering Binary Visual | question | s |
| Zero-Shot and Few-Shot Video | question | Answering with Multi-Modal Prompts |
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