Neural networks have shown tremendous growth in recent years to solve numerous
problems. Various types of neural networks have been introduced to deal with different types …

Object detection is a fundamental visual recognition problem in computer vision and has
been widely studied in the past decades. Visual object detection aims to find objects of …

Abstract Convolutional Neural Networks (CNNs) are the go-to model for computer vision.
Recently, attention-based networks, such as the Vision Transformer, have also become …

GAN inversion aims to invert a given image back into the latent space of a pretrained GAN
model so that the image can be faithfully reconstructed from the inverted code by the …

We propose a novel neural representation for videos (NeRV) which encodes videos in
neural networks. Unlike conventional representations that treat videos as frame sequences …

In the past few decades, artificial intelligence (AI) technology has experienced swift
developments, changing everyone's daily life and profoundly altering the course of human …

Adversarially trained generative models (GANs) have recently achieved compelling image
synthesis results. But despite early successes in using GANs for unsupervised …

Due to object detection's close relationship with video analysis and image understanding, it
has attracted much research attention in recent years. Traditional object detection methods …

Object detection, one of the most fundamental and challenging problems in computer vision,
seeks to locate object instances from a large number of predefined categories in natural …

With the transition of facial expression recognition (FER) from laboratory-controlled to
challenging in-the-wild conditions and the recent success of deep learning techniques in …