Zobrazeno 1 - 10
of 2 901
pro vyhledávání: '"KARAOGLU, A"'
The field of novel view synthesis from images has seen rapid advancements with the introduction of Neural Radiance Fields (NeRF) and more recently with 3D Gaussian Splatting. Gaussian Splatting became widely adopted due to its efficiency and ability
Externí odkaz:
http://arxiv.org/abs/2411.02229
Point cloud completion aims to recover the complete 3D shape of an object from partial observations. While approaches relying on synthetic shape priors achieved promising results in this domain, their applicability and generalizability to real-world
Externí odkaz:
http://arxiv.org/abs/2409.10180
In addition to color and textural information, geometry provides important cues for 3D scene reconstruction. However, current reconstruction methods only include geometry at the feature level thus not fully exploiting the geometric information. In co
Externí odkaz:
http://arxiv.org/abs/2408.15608
Existing methods in neural scene reconstruction utilize the Signed Distance Function (SDF) to model the density function. However, in indoor scenes, the density computed from the SDF for a sampled point may not consistently reflect its real importanc
Externí odkaz:
http://arxiv.org/abs/2408.15524
Designing high-quality indoor 3D scenes is important in many practical applications, such as room planning or game development. Conventionally, this has been a time-consuming process which requires both artistic skill and familiarity with professiona
Externí odkaz:
http://arxiv.org/abs/2407.20727
Autor:
Xing, Xiaoyan, Hu, Vincent Tao, Metzen, Jan Hendrik, Groh, Konrad, Karaoglu, Sezer, Gevers, Theo
This paper introduces a novel approach to illumination manipulation in diffusion models, addressing the gap in conditional image generation with a focus on lighting conditions. We conceptualize the diffusion model as a black-box image render and stra
Externí odkaz:
http://arxiv.org/abs/2407.20785
Autor:
Karaoglu, Ali
In contemporary imaging systems, achieving optimal auto-focus (AF) performance hinges on precise lens positioning. Extensive research has delved into refining algorithms for determining the ideal lens position across passive, active, and hybrid autof
Externí odkaz:
http://arxiv.org/abs/2407.01789
Autor:
Stilz, Florian Philipp, Karaoglu, Mert Asim, Tristram, Felix, Navab, Nassir, Busam, Benjamin, Ladikos, Alexander
Reconstruction of endoscopic scenes is an important asset for various medical applications, from post-surgery analysis to educational training. Neural rendering has recently shown promising results in endoscopic reconstruction with deforming tissue.
Externí odkaz:
http://arxiv.org/abs/2403.12198
Humans have a remarkable ability to perceive and reason about the world around them by understanding the relationships between objects. In this paper, we investigate the effectiveness of using such relationships for object detection and instance segm
Externí odkaz:
http://arxiv.org/abs/2310.07573
Unlike in natural images, in endoscopy there is no clear notion of an up-right camera orientation. Endoscopic videos therefore often contain large rotational motions, which require keypoint detection and description algorithms to be robust to these c
Externí odkaz:
http://arxiv.org/abs/2309.09563