Multimodal research in vision and language: A review of current and emerging trends
Deep Learning and its applications have cascaded impactful research and development
with a diverse range of modalities present in the real-world data. More recently, this has …
with a diverse range of modalities present in the real-world data. More recently, this has …
Counterfactual critic multi-agent training for scene graph generation
Scene graphs---objects as nodes and visual relationships as edges---describe the
whereabouts and interactions of objects in an image for comprehensive scene …
whereabouts and interactions of objects in an image for comprehensive scene …
Trends in integration of vision and language research: A survey of tasks, datasets, and methods
A Mogadala, M Kalimuthu, D Klakow - Journal of Artificial Intelligence …, 2021 - jair.org
Abstract Interest in Artificial Intelligence (AI) and its applications has seen unprecedented
growth in the last few years. This success can be partly attributed to the advancements made …
growth in the last few years. This success can be partly attributed to the advancements made …
Re-attention for visual question answering
A simultaneous understanding of questions and images is crucial in Visual Question
Answering (VQA). While the existing models have achieved satisfactory performance by …
Answering (VQA). While the existing models have achieved satisfactory performance by …
Visual relationship detection: A survey
Visual relationship detection (VRD) is one newly developed computer vision task, aiming to
recognize relations or interactions between objects in an image. It is a further learning task …
recognize relations or interactions between objects in an image. It is a further learning task …
CoG-DQA: Chain-of-Guiding Learning with Large Language Models for Diagram Question Answering
Abstract Diagram Question Answering (DQA) is a challenging task requiring models to
answer natural language questions based on visual diagram contexts. It serves as a crucial …
answer natural language questions based on visual diagram contexts. It serves as a crucial …
A human-like traffic scene understanding system: A survey
Autonomous vehicles, also known as self-driving cars, have the capability to perceive the
environment, locate its position, and safely drive to the destination without any human …
environment, locate its position, and safely drive to the destination without any human …
Scenegate: Scene-graph based co-attention networks for text visual question answering
Visual Question Answering (VQA) models fail catastrophically on questions related to the
reading of text-carrying images. However, TextVQA aims to answer questions by …
reading of text-carrying images. However, TextVQA aims to answer questions by …
DisAVR: Disentangled Adaptive Visual Reasoning Network for Diagram Question Answering
Diagram Question Answering (DQA) aims to correctly answer questions about given
diagrams, which demands an interplay of good diagram understanding and effective …
diagrams, which demands an interplay of good diagram understanding and effective …
Alignment-Guided Self-Supervised Learning for Diagram Question Answering
S Wang, L Zhang, W Wu, T Qin… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Diagram question answering (DQA), which is defined as answering natural language
questions according to the visual diagram context, has attracted attention and has recently …
questions according to the visual diagram context, has attracted attention and has recently …