Search Results for author:
Found 7 papers, 1 papers with code
HyperNST: Hyper-Networks for Neural Style Transfer
We present HyperNST; a neural style transfer (NST) technique for the artistic stylization of images, based on Hyper-networks and the StyleGAN2 architecture.
The Contextual Appointment Scheduling Problem
This study is concerned with the determination of optimal appointment times for a sequence of jobs with uncertain duration.
ALADIN: All Layer Adaptive Instance Normalization for Fine-grained Style Similarity
We present ALADIN (All Layer AdaIN); a novel architecture for searching images based on the similarity of their artistic style.
Multitask Text-to-Visual Embedding with Titles and Clickthrough Data
In this paper, we propose a new method for learning text-visual embedding using both image titles and click-through data from an image search engine.
Few-Shot Adversarial Domain Adaptation
This work provides a framework for addressing the problem of supervised domain adaptation with deep models.
Unified Deep Supervised Domain Adaptation and Generalization
This work provides a unified framework for addressing the problem of visual supervised domain adaptation and generalization with deep models.
Ranked #87 on
Domain Generalization
on PACS
Information Bottleneck Learning Using Privileged Information for Visual Recognition
The problem is challenging because of the intrinsic asymmetry caused by the missing auxiliary view during testing.
