207 citations · 212 across the 6 of their papers we have counts for
7 papers
Cosmos 3: Omnimodal World Models for Physical AI
NVIDIA, :, Aditi +293
We introduce Cosmos 3, a family of omnimodal world models designed to jointly process and generate language, image, video, audio, and action sequences within a unified mixture-of-t…
HyperNST: Hyper-Networks for Neural Style Transfer
Dan Ruta, Andrew Gilbert, Saeid Motiian +3
We present HyperNST; a neural style transfer (NST) technique for the artistic stylization of images, based on Hyper-networks and the StyleGAN2 architecture. Our contribution is a n…
The Contextual Appointment Scheduling Problem
Nima Salehi Sadghiani, Saeid Motiian
This study is concerned with the determination of optimal appointment times for a sequence of jobs with uncertain duration. We investigate the data-driven Appointment Scheduling Pr…
ALADIN: All Layer Adaptive Instance Normalization for Fine-grained Style Similarity
Dan Ruta, Saeid Motiian, Baldo Faieta +5
We present ALADIN (All Layer AdaIN); a novel architecture for searching images based on the similarity of their artistic style. Representation learning is critical to visual search…
Multitask Text-to-Visual Embedding with Titles and Clickthrough Data
Pranav Aggarwal, Zhe Lin, Baldo Faieta +1
Text-visual (or called semantic-visual) embedding is a central problem in vision-language research. It typically involves mapping of an image and a text description to a common fea…
Few-Shot Adversarial Domain Adaptation
Saeid Motiian, Quinn Jones, Seyed Mehdi Iranmanesh +1
This work provides a framework for addressing the problem of supervised domain adaptation with deep models. The main idea is to exploit adversarial learning to learn an embedded su…
Unified Deep Supervised Domain Adaptation and Generalization
Saeid Motiian, Marco Piccirilli, Donald A. Adjeroh +1
This work provides a unified framework for addressing the problem of visual supervised domain adaptation and generalization with deep models. The main idea is to exploit the Siames…