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Found 6 papers, 0 papers with code
Multi-Clue Reasoning with Memory Augmentation for Knowledge-based Visual Question Answering
Visual Question Answering (VQA) has emerged as one of the most challenging tasks in artificial intelligence due to its multi-modal nature.
Cross-Modal Reasoning with Event Correlation for Video Question Answering
Video Question Answering (VideoQA) is a very attractive and challenging research direction aiming to understand complex semantics of heterogeneous data from two domains, i. e., the spatio-temporal video content and the word sequence in question.
Continual Few-Shot Learning with Adversarial Class Storage
In this paper, we define a new problem called continual few-shot learning, in which tasks arrive sequentially and each task is associated with a few training samples.
Human Pose Transfer with Augmented Disentangled Feature Consistency
Deep generative models have made great progress in synthesizing images with arbitrary human poses and transferring poses of one person to others.
Hierarchical Graph Attention Network for Few-Shot Visual-Semantic Learning
Deep learning has made tremendous success in computer vision, natural language processing and even visual-semantic learning, which requires a huge amount of labeled training data.
Adversarial Meta-Learning
Meta-learning enables a model to learn from very limited data to undertake a new task.
