Multimodal image synthesis and editing: A survey and taxonomy
As information exists in various modalities in real world, effective interaction and fusion
among multimodal information plays a key role for the creation and perception of multimodal …
among multimodal information plays a key role for the creation and perception of multimodal …
A review on generative adversarial networks: Algorithms, theory, and applications
Generative adversarial networks (GANs) have recently become a hot research topic;
however, they have been studied since 2014, and a large number of algorithms have been …
however, they have been studied since 2014, and a large number of algorithms have been …
Egsde: Unpaired image-to-image translation via energy-guided stochastic differential equations
Score-based diffusion models (SBDMs) have achieved the SOTA FID results in unpaired
image-to-image translation (I2I). However, we notice that existing methods totally ignore the …
image-to-image translation (I2I). However, we notice that existing methods totally ignore the …
Ego-exo4d: Understanding skilled human activity from first-and third-person perspectives
Abstract We present Ego-Exo4D a diverse large-scale multimodal multiview video dataset
and benchmark challenge. Ego-Exo4D centers around simultaneously-captured egocentric …
and benchmark challenge. Ego-Exo4D centers around simultaneously-captured egocentric …
Image-to-image translation: Methods and applications
Image-to-image translation (I2I) aims to transfer images from a source domain to a target
domain while preserving the content representations. I2I has drawn increasing attention and …
domain while preserving the content representations. I2I has drawn increasing attention and …
Attention, please! A survey of neural attention models in deep learning
A de Santana Correia, EL Colombini - Artificial Intelligence Review, 2022 - Springer
In humans, Attention is a core property of all perceptual and cognitive operations. Given our
limited ability to process competing sources, attention mechanisms select, modulate, and …
limited ability to process competing sources, attention mechanisms select, modulate, and …
Unbalanced feature transport for exemplar-based image translation
Despite the great success of GANs in images translation with different conditioned inputs
such as semantic segmentation and edge map, generating high-fidelity images with …
such as semantic segmentation and edge map, generating high-fidelity images with …
Generative Adversarial Networks in the built environment: A comprehensive review of the application of GANs across data types and scales
Abstract Generative Adversarial Networks (GANs) are a type of deep neural network that
have achieved many state-of-the-art results for generative tasks. GANs can be useful in the …
have achieved many state-of-the-art results for generative tasks. GANs can be useful in the …
Transformer-based attention networks for continuous pixel-wise prediction
While convolutional neural networks have shown a tremendous impact on various computer
vision tasks, they generally demonstrate limitations in explicitly modeling long-range …
vision tasks, they generally demonstrate limitations in explicitly modeling long-range …
LANet: Local attention embedding to improve the semantic segmentation of remote sensing images
The trade-off between feature representation power and spatial localization accuracy is
crucial for the dense classification/semantic segmentation of remote sensing images (RSIs) …
crucial for the dense classification/semantic segmentation of remote sensing images (RSIs) …