activity
20112022
most citedmustGAN: Multi-Stream Generative Adversarial Networks for MR Image Synthesis

10 citations · 19 across the 7 of their papers we have counts for

collaborators

17 papers

cs.CL20221 cited

Detecting Euphemisms with Literal Descriptions and Visual Imagery

İlker Kesen, Aykut Erdem, Erkut Erdem +1

This paper describes our two-stage system for the Euphemism Detection shared task hosted by the 3rd Workshop on Figurative Language Processing in conjunction with EMNLP 2022. Euphe…

cs.CV2022

Disentangling Content and Motion for Text-Based Neural Video Manipulation

Levent Karacan, Tolga Kerimoğlu, İsmail İnan +3

Giving machines the ability to imagine possible new objects or scenes from linguistic descriptions and produce their realistic renderings is arguably one of the most challenging pr…

cs.CV2022

Perception-Distortion Trade-off in the SR Space Spanned by Flow Models

Cansu Korkmaz, A. Murat Tekalp, Zafer Dogan +2

Flow-based generative super-resolution (SR) models learn to produce a diverse set of feasible SR solutions, called the SR space. Diversity of SR solutions increases with the temper…

cs.CV20225 cited

Stochastic Video Prediction with Structure and Motion

Adil Kaan Akan, Sadra Safadoust, Fatma Güney

While stochastic video prediction models enable future prediction under uncertainty, they mostly fail to model the complex dynamics of real-world scenes. For example, they cannot p…

cs.CV2021

SLAMP: Stochastic Latent Appearance and Motion Prediction

Adil Kaan Akan, Erkut Erdem, Aykut Erdem +1

Motion is an important cue for video prediction and often utilized by separating video content into static and dynamic components. Most of the previous work utilizing motion is det…

cs.CV2021

A Gated Fusion Network for Dynamic Saliency Prediction

Aysun Kocak, Erkut Erdem, Aykut Erdem

Predicting saliency in videos is a challenging problem due to complex modeling of interactions between spatial and temporal information, especially when ever-changing, dynamic natu…