Abstract 3D target detection is a research hotspot in recent years. In the field of autonomous
driving, 3D target detection is mainly targeted at outdoor scenes that the camera height is …

In recent years, supervised video summarization has made tremendous progress with
treating it as a sequence-to-sequence learning task. However, traditional recurrent neural …

Compared with traditional methods, the action recognition model based on 3D convolutional
deep neural network captures spatio-temporal features more accurately, resulting in higher …

Temporal action detection is a challenging task in video understanding, due to the
complexity of the background and rich action content impacting high-quality temporal …

The coarse-to-fine architecture is a benchmark method designed to enhance the accuracy of
3D medical landmark detection. However, incorporating 3D convolutional neural networks …

Temporal action proposal generation is a fundamental yet challenging to locate the temporal
action in untrimmed videos. Although current proposal generation methods can generate the …

Neural network filter pruning has demonstrated its effectiveness for deploying the models
with fewer resources and efficient inference. However, the process of pruning networks in …

The intelligent recognition of human behavior and action in massive video data is the key
application direction in the field of artificial intelligence. With the development of intelligent …