Digital fashion: A systematic literature review. A perspective on marketing and communication
Research in the overlapping area between Fashion and Information and Communication
Technologies–hereafter referred to as “Digital Fashion”–is growing and attracting the …
Technologies–hereafter referred to as “Digital Fashion”–is growing and attracting the …
Fashion meets computer vision: A survey
Fashion is the way we present ourselves to the world and has become one of the world's
largest industries. Fashion, mainly conveyed by vision, has thus attracted much attention …
largest industries. Fashion, mainly conveyed by vision, has thus attracted much attention …
Underwater scene prior inspired deep underwater image and video enhancement
In underwater scenes, wavelength-dependent light absorption and scattering degrade the
visibility of images and videos. The degraded underwater images and videos affect the …
visibility of images and videos. The degraded underwater images and videos affect the …
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 …
Benchmark analysis of jetson tx2, jetson nano and raspberry pi using deep-cnn
Hardware, low power consumption, high accuracy and performance are crucial factors for
deep learning applications. High level graphics processing units (GPU) are commonly used …
deep learning applications. High level graphics processing units (GPU) are commonly used …
Logic-induced diagnostic reasoning for semi-supervised semantic segmentation
Recent advances in semi-supervised semantic segmentation have been heavily reliant on
pseudo labeling to compensate for limited labeled data, disregarding the valuable relational …
pseudo labeling to compensate for limited labeled data, disregarding the valuable relational …
Crowdpose: Efficient crowded scenes pose estimation and a new benchmark
Multi-person pose estimation is fundamental to many computer vision tasks and has made
significant progress in recent years. However, few previous methods explored the problem …
significant progress in recent years. However, few previous methods explored the problem …
Learning human-object interactions by graph parsing neural networks
This paper addresses the task of detecting and recognizing human-object interactions (HOI)
in images and videos. We introduce the Graph Parsing Neural Network (GPNN), a …
in images and videos. We introduce the Graph Parsing Neural Network (GPNN), a …
Learning with average precision: Training image retrieval with a listwise loss
Image retrieval can be formulated as a ranking problem where the goal is to order database
images by decreasing similarity to the query. Recent deep models for image retrieval have …
images by decreasing similarity to the query. Recent deep models for image retrieval have …
Deepfashion2: A versatile benchmark for detection, pose estimation, segmentation and re-identification of clothing images
Understanding fashion images has been advanced by benchmarks with rich annotations
such as DeepFashion, whose labels include clothing categories, landmarks, and consumer …
such as DeepFashion, whose labels include clothing categories, landmarks, and consumer …