High-Resolution Image Synthesis with Latent Diffusion Models
By decomposing the image formation process into a sequential application of denoising autoencoders, diffusion models (DMs) achieve state-of-the-art synthesis results on image da...
Publications
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309 publications
Conceptualizing, Measuring, and Managing Customer-Based Brand Equity
The author presents a conceptual model of brand equity from the perspective of the individual consumer. Customer-based brand equity is defined as the differential effect of bran...
Learning Deep Features for Discriminative Localization
In this work, we revisit the global average pooling layer proposed in [13], and shed light on how it explicitly enables the convolutional neural network (CNN) to have remarkable...
Active contours without edges
We propose a new model for active contours to detect objects in a given image, based on techniques of curve evolution, Mumford-Shah (1989) functional for segmentation and level ...
Marching cubes: A high resolution 3D surface construction algorithm
El uso de vóxeles en aplicaciones interactivas se aplica desde hace décadas, con múltiples maneras de implementación de acuerdo al hardware para el que se desarrollaba y los obj...
Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions
This paper presents an overview of the field of recommender systems and describes the current generation of recommendation methods that are usually classified into the following...
ORB: An efficient alternative to SIFT or SURF
Feature matching is at the base of many computer vision problems, such as object recognition or structure from motion. Current methods rely on costly descriptors for detection a...
Object Detection with Discriminatively Trained Part-Based Models
We describe an object detection system based on mixtures of multiscale deformable part models. Our system is able to represent highly variable object classes and achieves state-...
YOLOv7: Trainable Bag-of-Freebies Sets New State-of-the-Art for Real-Time Object Detectors
Real-time object detection is one of the most important research topics in computer vision. As new approaches regarding architecture optimization and training optimization are c...