Zobrazeno 1 - 10
of 7 655
pro vyhledávání: '"Dundar A"'
Publikováno v:
Sanamed, Vol 18, Iss 2, Pp 105-112 (2023)
Introduction: Distal femoral shaft fractures are characterized by their increasing incidence and complexity, presenting a significant challenge in management. The objective of this retrospective study was to compare the clinical and radiological resu
Externí odkaz:
https://doaj.org/article/ae5198f520fb458e9e88710b889e4cb7
3D GAN inversion aims to project a single image into the latent space of a 3D Generative Adversarial Network (GAN), thereby achieving 3D geometry reconstruction. While there exist encoders that achieve good results in 3D GAN inversion, they are predo
Externí odkaz:
http://arxiv.org/abs/2409.20530
Autor:
Ekin, Yigit, Yildirim, Ahmet Burak, Caglar, Erdem Eren, Erdem, Aykut, Erdem, Erkut, Dundar, Aysegul
Advanced image editing techniques, particularly inpainting, are essential for seamlessly removing unwanted elements while preserving visual integrity. Traditional GAN-based methods have achieved notable success, but recent advancements in diffusion m
Externí odkaz:
http://arxiv.org/abs/2406.09368
Generative Adversarial Networks (GANs) have emerged as powerful tools for high-quality image generation and real image editing by manipulating their latent spaces. Recent advancements in GANs include 3D-aware models such as EG3D, which feature effici
Externí odkaz:
http://arxiv.org/abs/2404.03632
StyleGAN models show editing capabilities via their semantically interpretable latent organizations which require successful GAN inversion methods to edit real images. Many works have been proposed for inverting images into StyleGAN's latent space. H
Externí odkaz:
http://arxiv.org/abs/2312.11422
Autor:
Sivuk, Hakan, Dundar, Aysegul
Semantic image editing requires inpainting pixels following a semantic map. It is a challenging task since this inpainting requires both harmony with the context and strict compliance with the semantic maps. The majority of the previous methods propo
Externí odkaz:
http://arxiv.org/abs/2309.13975
Recent inversion methods have shown that real images can be inverted into StyleGAN's latent space and numerous edits can be achieved on those images thanks to the semantically rich feature representations of well-trained GAN models. However, extensiv
Externí odkaz:
http://arxiv.org/abs/2307.15033
This paper presents a method to reconstruct high-quality textured 3D models from single images. Current methods rely on datasets with expensive annotations; multi-view images and their camera parameters. Our method relies on GAN generated multi-view
Externí odkaz:
http://arxiv.org/abs/2305.11102
Image inpainting task refers to erasing unwanted pixels from images and filling them in a semantically consistent and realistic way. Traditionally, the pixels that are wished to be erased are defined with binary masks. From the application point of v
Externí odkaz:
http://arxiv.org/abs/2304.03246
Estimating 3D human texture from a single image is essential in graphics and vision. It requires learning a mapping function from input images of humans with diverse poses into the parametric (UV) space and reasonably hallucinating invisible parts. T
Externí odkaz:
http://arxiv.org/abs/2303.03471