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of 32
pro vyhledávání: '"Athar, ShahRukh"'
Shadow boundaries can be confused with material boundaries as both exhibit sharp changes in luminance or contrast within a scene. However, shadows do not modify the intrinsic color or texture of surfaces. Therefore, on both sides of shadow edges trav
Externí odkaz:
http://arxiv.org/abs/2409.06848
Creating photorealistic avatars for individuals traditionally involves extensive capture sessions with complex and expensive studio devices like the LightStage system. While recent strides in neural representations have enabled the generation of phot
Externí odkaz:
http://arxiv.org/abs/2407.19593
Creating controllable 3D human portraits from casual smartphone videos is highly desirable due to their immense value in AR/VR applications. The recent development of 3D Gaussian Splatting (3DGS) has shown improvements in rendering quality and traini
Externí odkaz:
http://arxiv.org/abs/2402.03723
Autor:
Sevastopolsky, Artem, Grassal, Philip-William, Giebenhain, Simon, Athar, ShahRukh, Verdoliva, Luisa, Niessner, Matthias
Current advances in human head modeling allow to generate plausible-looking 3D head models via neural representations. Nevertheless, constructing complete high-fidelity head models with explicitly controlled animation remains an issue. Furthermore, c
Externí odkaz:
http://arxiv.org/abs/2312.14140
Autor:
Athar, ShahRukh, Shu, Zhixin, Xu, Zexiang, Luan, Fujun, Bi, Sai, Sunkavalli, Kalyan, Samaras, Dimitris
Recent advances in Neural Radiance Fields (NeRFs) have made it possible to reconstruct and reanimate dynamic portrait scenes with control over head-pose, facial expressions and viewing direction. However, training such models assumes photometric cons
Externí odkaz:
http://arxiv.org/abs/2309.11009
Volumetric neural rendering methods, such as neural radiance fields (NeRFs), have enabled photo-realistic novel view synthesis. However, in their standard form, NeRFs do not support the editing of objects, such as a human head, within a scene. In thi
Externí odkaz:
http://arxiv.org/abs/2206.06481
Autor:
Athar, Shahrukh, Wang, Zhou
In practical media distribution systems, visual content usually undergoes multiple stages of quality degradation along the delivery chain, but the pristine source content is rarely available at most quality monitoring points along the chain to serve
Externí odkaz:
http://arxiv.org/abs/2110.14899
Banding or false contour is an annoying visual artifact whose impact is even more pronounced in ultra high definition, high dynamic range, and wide colour gamut visual content, which is becoming increasingly popular. Since users associate a heightene
Externí odkaz:
http://arxiv.org/abs/2110.08569
The enormous space and diversity of natural images is usually represented by a few small-scale human-rated image quality assessment (IQA) datasets. This casts great challenges to deep neural network (DNN) based blind IQA (BIQA), which requires large-
Externí odkaz:
http://arxiv.org/abs/2109.12161
We present SIDER(Single-Image neural optimization for facial geometric DEtail Recovery), a novel photometric optimization method that recovers detailed facial geometry from a single image in an unsupervised manner. Inspired by classical techniques of
Externí odkaz:
http://arxiv.org/abs/2108.05465