1 citations · 3 across the 4 of their papers we have counts for
7 papers
3D-LatentMapper: View Agnostic Single-View Reconstruction of 3D Shapes
Alara Dirik, Pinar Yanardag
Computer graphics, 3D computer vision and robotics communities have produced multiple approaches to represent and generate 3D shapes, as well as a vast number of use cases. However…
Fantastic Style Channels and Where to Find Them: A Submodular Framework for Discovering Diverse Directions in GANs
Enis Simsar, Umut Kocasari, Ezgi Gülperi Er +1
The discovery of interpretable directions in the latent spaces of pre-trained GAN models has recently become a popular topic. In particular, StyleGAN2 has enabled various image gen…
Discovering Multiple and Diverse Directions for Cognitive Image Properties
Umut Kocasari, Alperen Bag, Oguz Kaan Yuksel +1
Recent research has shown that it is possible to find interpretable directions in the latent spaces of pre-trained GANs. These directions enable controllable generation and support…
FairStyle: Debiasing StyleGAN2 with Style Channel Manipulations
Cemre Karakas, Alara Dirik, Eylul Yalcinkaya +1
Recent advances in generative adversarial networks have shown that it is possible to generate high-resolution and hyperrealistic images. However, the images produced by GANs are on…
Text and Image Guided 3D Avatar Generation and Manipulation
Zehranaz Canfes, M. Furkan Atasoy, Alara Dirik +1
The manipulation of latent space has recently become an interesting topic in the field of generative models. Recent research shows that latent directions can be used to manipulate…
Graph2Pix: A Graph-Based Image to Image Translation Framework
Dilara Gokay, Enis Simsar, Efehan Atici +3
In this paper, we propose a graph-based image-to-image translation framework for generating images. We use rich data collected from the popular creativity platform Artbreeder (http…