Understanding GANs: Fundamentals, variants, training challenges, applications, and open problems
Generative adversarial networks (GANs), a novel framework for training generative models
in an adversarial setup, have attracted significant attention in recent years. The two …
in an adversarial setup, have attracted significant attention in recent years. The two …
Unsupervised image-to-image translation: A review
Supervised image-to-image translation has been proven to generate realistic images with
sharp details and to have good quantitative performance. Such methods are trained on a …
sharp details and to have good quantitative performance. Such methods are trained on a …
Only a matter of style: Age transformation using a style-based regression model
The task of age transformation illustrates the change of an individual's appearance over
time. Accurately modeling this complex transformation over an input facial image is …
time. Accurately modeling this complex transformation over an input facial image is …
Uvcgan: Unet vision transformer cycle-consistent gan for unpaired image-to-image translation
Unpaired image-to-image translation has broad applications in art, design, and scientific
simulations. One early breakthrough was CycleGAN that emphasizes one-to-one map**s …
simulations. One early breakthrough was CycleGAN that emphasizes one-to-one map**s …
Local class-specific and global image-level generative adversarial networks for semantic-guided scene generation
In this paper, we address the task of semantic-guided scene generation. One open
challenge widely observed in global image-level generation methods is the difficulty of …
challenge widely observed in global image-level generation methods is the difficulty of …
AI co-pilot bronchoscope robot
J Zhang, L Liu, P **ang, Q Fang, X Nie, H Ma… - Nature …, 2024 - nature.com
The unequal distribution of medical resources and scarcity of experienced practitioners
confine access to bronchoscopy primarily to well-equipped hospitals in developed regions …
confine access to bronchoscopy primarily to well-equipped hospitals in developed regions …
Ic-gan: An improved conditional generative adversarial network for rgb-to-ir image translation with applications to forest fire monitoring
This paper introduces a novel Deep Learning (DL) architecture for inferring temperature
information from aerial true-color RGB images by transforming them into Infrared Radiation …
information from aerial true-color RGB images by transforming them into Infrared Radiation …
Dehaze-AGGAN: Unpaired remote sensing image dehazing using enhanced attention-guide generative adversarial networks
Remote sensing image dehazing is of great scientific interest and application value in both
military and civil fields. In this article, we propose an enhanced attention-guide generative …
military and civil fields. In this article, we propose an enhanced attention-guide generative …
Copyright protection and accountability of generative ai: Attack, watermarking and attribution
Generative AI (eg, Generative Adversarial Networks–GANs) has become increasingly
popular in recent years. However, Generative AI introduces significant concerns regarding …
popular in recent years. However, Generative AI introduces significant concerns regarding …
Edge guided GANs with multi-scale contrastive learning for semantic image synthesis
We propose a novel e dge guided g enerative a dversarial n etwork with c ontrastive
learning (ECGAN) for the challenging semantic image synthesis task. Although considerable …
learning (ECGAN) for the challenging semantic image synthesis task. Although considerable …