Image captioning aims to automatically generate a natural language description of a given
image, and most state-of-the-art models have adopted an encoder-decoder framework. The …

Medical image segmentation has the priori guiding significance for clinical diagnosis and
treatment. In the past ten years, a large number of experimental facts have proved the great …

In this work, we present a novel multi-scale feature fusion network (M-FFN) for image
captioning task to incorporate discriminative features and scene contextual information of an …

Occlusions present a great challenge for pedestrian detection in practical applications. In
this paper, we propose a novel approach to simultaneous pedestrian detection and …

It is difficult to construct a data collection including all possible combinations of human
actions and interacting objects due to the combinatorial nature of human-object interactions …

Extracting effective spatial-temporal information is significantly important for video-based
action recognition. Recently 3D convolutional neural networks (3D CNNs) that could …

Despite outstanding performance in image recognition, convolutional neural networks
(CNNs) do not yet achieve the same impressive results on action recognition in videos. This …

Deep-learning-based super-resolution (SR) methods have been extensively studied and
have achieved significant performance with deep convolutional neural networks. However …

Action visual tempo characterizes the dynamics and the temporal scale of an action, which is
helpful to distinguish human actions that share high similarities in visual dynamics and …

Remote sensing images have been widely used in military, national defense, disaster
emergency response, ecological environment monitoring, among other applications …