Capsule networks (CapsNets) have been known difficult to develop a deeper architecture,
which is desirable for high performance in the deep learning era, due to the complex …

Keyword spotting is an important research field because it plays a key role in device wake-
up and user interaction on smart devices. However, it is challenging to minimize errors while …

Solving grounded language tasks often requires reasoning about relationships between
objects in the context of a given task. For example, to answer the question" What color is the …

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 …

Compositional generalization is a key challenge in grounding natural language to visual
perception. While deep learning models have achieved great success in multimodal tasks …

Relational Networks (RN), as one of the most widely used relational reasoning techniques,
have achieved great success in many applications such as action and image analysis …

Convolutional neural networks (CNNs) achieve translational invariance by using pooling
operations. However, the operations do not preserve the spatial relationships in the learned …

Rather than performing inefficient local iterative routing between adjacent capsule layers,
we propose an alternative global view based on representing the inherent uncertainty in part …

In this paper, we propose a deep relational network which exploits multi-scale information of
facial images for kinship verification. Unlike most existing deep learning based facial kinship …

Visual reasoning is a special kind of visual question answering, which is essentially multi-
step and compositional, and also requires intensive text-visual interaction. The most …