Dynamic neural networks are a recent technique that promises a remedy fo...
Recently, long-tailed image classification harvests lots of research
att...
Full-reference point cloud quality assessment (FR-PCQA) aims to infer th...
Temporal action localization aims at localizing action instances from
un...
Online action detection has attracted increasing research interests in r...
Weakly supervised temporal action localization aims at learning the
inst...
Reusing features in deep networks through dense connectivity is an effec...
Dynamic neural network is an emerging research topic in deep learning.
C...
Due to the need to store the intermediate activations for back-propagati...
The accuracy of deep convolutional neural networks (CNNs) generally impr...
A fine-grained analysis of the cache-enabled networks is crucial for sys...
Most of the current action localization methods follow an anchor-based
p...
Weakly supervised temporal action localization is a newly emerging yet w...
In this paper, we focus on the meta distribution for the cache-enabled
n...
Emergence of various types of services has brought about explosive growt...
Recently, adaptive inference is gaining increasing attention due to its ...
In recent years, optimization of the success transmission probability in...
In this report, we introduce the Winner method for HACS Temporal Action
...
Gaussian process regression is a machine learning approach which has bee...