Vqa and visual reasoning: An overview of recent datasets, methods and challenges
Artificial Intelligence (AI) and its applications have sparked extraordinary interest in recent
years. This achievement can be ascribed in part to advances in AI subfields including …
years. This achievement can be ascribed in part to advances in AI subfields including …
Dual self-attention with co-attention networks for visual question answering
Abstract Visual Question Answering (VQA) as an important task in understanding vision and
language has been proposed and aroused wide interests. In previous VQA methods …
language has been proposed and aroused wide interests. In previous VQA methods …
A survey of methods, datasets and evaluation metrics for visual question answering
Abstract Visual Question Answering (VQA) is a multi-disciplinary research problem that has
captured the attention of both computer vision as well as natural language processing …
captured the attention of both computer vision as well as natural language processing …
A survey of efficient fine-tuning methods for Vision-Language Models—Prompt and Adapter
J Xing, J Liu, J Wang, L Sun, X Chen, X Gu… - Computers & Graphics, 2024 - Elsevier
Abstract Vision Language Model (VLM) is a popular research field located at the fusion of
computer vision and natural language processing (NLP). With the emergence of transformer …
computer vision and natural language processing (NLP). With the emergence of transformer …
An improved attention and hybrid optimization technique for visual question answering
Abstract In Visual Question Answering (VQA), an attention mechanism has a critical role in
specifying the different objects present in an image or tells the machine where to focus by …
specifying the different objects present in an image or tells the machine where to focus by …
Image captioning improved visual question answering
Abstract Both Visual Question Answering (VQA) and image captioning are the problems
which involve Computer Vision (CV) and Natural Language Processing (NLP) domains. In …
which involve Computer Vision (CV) and Natural Language Processing (NLP) domains. In …
Positional attention guided transformer-like architecture for visual question answering
A Mao, Z Yang, K Lin, J Xuan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Transformer architectures have recently been introduced into the field of visual question
answering (VQA), due to their powerful capabilities of information extraction and fusion …
answering (VQA), due to their powerful capabilities of information extraction and fusion …
Counting-based visual question answering with serial cascaded attention deep learning
T MeshuWelde, L Liao - Pattern Recognition, 2023 - Elsevier
The counting-based questions play a major part in Visual Question Answering (VQA), the
most challenging factor is counting the different objects present in the images. Recently …
most challenging factor is counting the different objects present in the images. Recently …
Protein–ligand binding affinity prediction with edge awareness and supervised attention
Y Gu, X Zhang, A Xu, W Chen, K Liu, L Wu, S Mo, Y Hu… - Iscience, 2023 - cell.com
Accurate prediction of protein–ligand binding affinity is crucial in structure-based drug
design but remains some challenges even with recent advances in deep learning:(1) …
design but remains some challenges even with recent advances in deep learning:(1) …
A question-guided multi-hop reasoning graph network for visual question answering
Abstract Visual Question Answering (VQA) requires reasoning about the visually-grounded
relations in the image and question context. A crucial aspect of solving complex questions is …
relations in the image and question context. A crucial aspect of solving complex questions is …