101 citations · 151 across the 9 of their papers we have counts for
11 papers
Learning Disentangled Prompts for Compositional Image Synthesis
Kihyuk Sohn, Albert Shaw, Yuan Hao +5
We study domain-adaptive image synthesis, the problem of teaching pretrained image generative models a new style or concept from as few as one image to synthesize novel images, to…
Visual Prompt Tuning for Generative Transfer Learning
Kihyuk Sohn, Yuan Hao, José Lezama +5
Transferring knowledge from an image synthesis model trained on a large dataset is a promising direction for learning generative image models from various domains efficiently. Whil…
Learning Furniture Compatibility with Graph Neural Networks
Luisa F. Polania, Mauricio Flores, Yiran Li +1
We propose a graph neural network (GNN) approach to the problem of predicting the stylistic compatibility of a set of furniture items from images. While most existing results are b…
Deep Adaptive Wavelet Network
Maria Ximena Bastidas Rodriguez, Adrien Gruson, Luisa F. Polania +4
Even though convolutional neural networks have become the method of choice in many fields of computer vision, they still lack interpretability and are usually designed manually in…
Graph Neural Networks for Image Understanding Based on Multiple Cues: Group Emotion Recognition and Event Recognition as Use Cases
Xin Guo, Luisa F. Polania, Bin Zhu +2
A graph neural network (GNN) for image understanding based on multiple cues is proposed in this paper. Compared to traditional feature and decision fusion approaches that neglect t…
Learning fashion compatibility across apparel categories for outfit recommendation
Luisa F. Polania, Satyajit Gupte
This paper addresses the problem of generating recommendations for completing the outfit given that a user is interested in a particular apparel item. The proposed method is based…
Ordinal Regression using Noisy Pairwise Comparisons for Body Mass Index Range Estimation
Luisa Polania, Dongning Wang, Glenn Fung
Ordinal regression aims to classify instances into ordinal categories. In this paper, body mass index (BMI) category estimation from facial images is cast as an ordinal regression…
Compressed Sensing ECG using Restricted Boltzmann Machines
Luisa Polania, Rafael Plaza
Recently, it has been shown that compressed sensing (CS) has the potential to lower energy consumption in wireless electrocardiogram (ECG) systems. By reducing the number of acquir…
Smile detection in the wild based on transfer learning
Xin Guo, Luisa F. Polanía, Kenneth E. Barner
Smile detection from unconstrained facial images is a specialized and challenging problem. As one of the most informative expressions, smiles convey basic underlying emotions, such…
Exploiting Restricted Boltzmann Machines and Deep Belief Networks in Compressed Sensing
Luisa F. Polania, Kenneth E. Barner
This paper proposes a CS scheme that exploits the representational power of restricted Boltzmann machines and deep learning architectures to model the prior distribution of the spa…
Exploiting Prior Knowledge in Compressed Sensing Wireless ECG Systems
Luisa F. Polania, Rafael E. Carrillo, Manuel Blanco-Velasco +1
Recent results in telecardiology show that compressed sensing (CS) is a promising tool to lower energy consumption in wireless body area networks for electrocardiogram (ECG) monito…