The standard approach to tackling computer vision problems is to train deep convolutional
neural network (CNN) models using large-scale image datasets that are representative of …

AI-generated content (AIGC) methods aim to produce text, images, videos, 3D assets, and
other media using AI algorithms. Due to its wide range of applications and the demonstrated …

Conditional image-to-video (cI2V) generation aims to synthesize a new plausible video
starting from an image (eg, a person's face) and a condition (eg, an action class label like …

Videos are created to express emotion, exchange information, and share experiences.
Video synthesis has intrigued researchers for a long time. Despite the rapid progress driven …

The rapid advancement of deep learning models that can generate and synthesis hyper-
realistic videos known as Deepfakes and their ease of access to the general public have …

The generative adversarial network (GAN) framework has emerged as a powerful tool for
various image and video synthesis tasks, allowing the synthesis of visual content in an …

VLN-CE is a recently released embodied task, where AI agents need to navigate a freely
traversable environment to reach a distant target location, given language instructions. It …

We present an approach to enhancing the realism of synthetic images. The images are
enhanced by a convolutional network that leverages intermediate representations produced …

Abstract 3D city generation is a desirable yet challenging task since humans are more
sensitive to structural distortions in urban environments. Additionally generating 3D cities is …

Recent advances in visually-induced audio generation are based on sampling short, low-
fidelity, and one-class sounds. Moreover, sampling 1 second of audio from the state-of-the …