3D human pose estimation has been researched for decades with promising
...
Millimeter-wave(mmWave) technology has emerged as a promising enabler fo...
Fine-tuning visual models has been widely shown promising performance on...
Predicting the next location is a highly valuable and common need in man...
Multi-instance learning (MIL) is an effective paradigm for whole-slide
p...
Generating motion in line with text has attracted increasing attention
n...
Since the release of various large-scale natural language processing (NL...
The objective of this work is to explore how to effectively and efficien...
Learned video compression has recently emerged as an essential research ...
Recent high-performing Human-Object Interaction (HOI) detection techniqu...
Finding relevant moments and highlights in videos according to natural
l...
Translating visual data into natural language is essential for machines ...
As a technically challenging topic, visual storytelling aims at generati...
The task of instance segmentation in remote sensing images, aiming at
pe...
Contrastive learning, which aims at minimizing the distance between posi...
Nowadays, Internet of Video Things (IoVT) grows rapidly in terms of quan...
In multi-cell non-orthogonal multiple access (NOMA) systems, designing a...
The task of classifying mammograms is very challenging because the lesio...
Limited backhaul bandwidth and blockage effects are two main factors lim...
We consider the problem of Human-Object Interaction (HOI) Detection, whi...
Many semantic events in team sport activities e.g. basketball often invo...
Many important classification problems, such as object classification, s...
The learning of Transformation-Equivariant Representations (TERs), which...
In multi-person videos, especially team sport videos, a semantic event i...
Non-orthogonal multiple access (NOMA) has shown potential for scalable
m...
Unsupervised image translation, which aims in translating two independen...
Modeling statistical regularities is the problem of representing the pix...
Recently, non-orthogonal multiple access (NOMA) has been proposed to ach...
Deep convolutional neural networks (CNN) have recently been shown to gen...
In this work we study the problem of network morphism, an effective lear...
Visual storytelling aims to generate human-level narrative language (i.e...
We present in this paper a systematic study on how to morph a well-train...