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Face Anything: 4D Face Reconstruction from Any Image Sequence
Umut Kocasari, Simon Giebenhain, Richard Shaw +1
Accurate reconstruction and tracking of dynamic human faces from image sequences is challenging because non-rigid deformations, expression changes, and viewpoint variations occur s…
G3DST: Generalizing 3D Style Transfer with Neural Radiance Fields across Scenes and Styles
Adil Meric, Umut Kocasari, Matthias Nießner +1
Neural Radiance Fields (NeRF) have emerged as a powerful tool for creating highly detailed and photorealistic scenes. Existing methods for NeRF-based 3D style transfer need extensi…
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…
StyleMC: Multi-Channel Based Fast Text-Guided Image Generation and Manipulation
Umut Kocasari, Alara Dirik, Mert Tiftikci +1
Discovering meaningful directions in the latent space of GANs to manipulate semantic attributes typically requires large amounts of labeled data. Recent work aims to overcome this…
Exploring Latent Dimensions of Crowd-sourced Creativity
Umut Kocasari, Alperen Bag, Efehan Atici +1
Recently, the discovery of interpretable directions in the latent spaces of pre-trained GANs has become a popular topic. While existing works mostly consider directions for semanti…