Zobrazeno 1 - 10
of 152
pro vyhledávání: '"Bergman, P. W."'
Neural radiance fields (NeRFs) have emerged as an effective method for novel-view synthesis and 3D scene reconstruction. However, conventional training methods require access to all training views during scene optimization. This assumption may be pro
Externí odkaz:
http://arxiv.org/abs/2309.01811
Autor:
Xu, Yinghao, Yifan, Wang, Bergman, Alexander W., Chai, Menglei, Zhou, Bolei, Wetzstein, Gordon
Access to high-quality and diverse 3D articulated digital human assets is crucial in various applications, ranging from virtual reality to social platforms. Generative approaches, such as 3D generative adversarial networks (GANs), are rapidly replaci
Externí odkaz:
http://arxiv.org/abs/2307.05462
The ability to generate diverse 3D articulated head avatars is vital to a plethora of applications, including augmented reality, cinematography, and education. Recent work on text-guided 3D object generation has shown great promise in addressing thes
Externí odkaz:
http://arxiv.org/abs/2307.04859
Autor:
Chan, Eric R., Nagano, Koki, Chan, Matthew A., Bergman, Alexander W., Park, Jeong Joon, Levy, Axel, Aittala, Miika, De Mello, Shalini, Karras, Tero, Wetzstein, Gordon
We present a diffusion-based model for 3D-aware generative novel view synthesis from as few as a single input image. Our model samples from the distribution of possible renderings consistent with the input and, even in the presence of ambiguity, is c
Externí odkaz:
http://arxiv.org/abs/2304.02602
Capturing images is a key part of automation for high-level tasks such as scene text recognition. Low-light conditions pose a challenge for high-level perception stacks, which are often optimized on well-lit, artifact-free images. Reconstruction meth
Externí odkaz:
http://arxiv.org/abs/2303.04291
Autor:
Bergman, Alexander W., Kellnhofer, Petr, Yifan, Wang, Chan, Eric R., Lindell, David B., Wetzstein, Gordon
Unsupervised learning of 3D-aware generative adversarial networks (GANs) using only collections of single-view 2D photographs has very recently made much progress. These 3D GANs, however, have not been demonstrated for human bodies and the generated
Externí odkaz:
http://arxiv.org/abs/2206.14314
Novel view synthesis is a long-standing problem in machine learning and computer vision. Significant progress has recently been made in developing neural scene representations and rendering techniques that synthesize photorealistic images from arbitr
Externí odkaz:
http://arxiv.org/abs/2106.14942
Publikováno v:
IEEE Transactions on Visualization and Computer Graphics 2022
Understanding and modeling the dynamics of human gaze behavior in 360$^\circ$ environments is a key challenge in computer vision and virtual reality. Generative adversarial approaches could alleviate this challenge by generating a large number of pos
Externí odkaz:
http://arxiv.org/abs/2103.13922
Autor:
Sitzmann, Vincent, Martel, Julien N. P., Bergman, Alexander W., Lindell, David B., Wetzstein, Gordon
Implicitly defined, continuous, differentiable signal representations parameterized by neural networks have emerged as a powerful paradigm, offering many possible benefits over conventional representations. However, current network architectures for
Externí odkaz:
http://arxiv.org/abs/2006.09661
Shaping codes are used to encode information for use on channels with cost constraints. Applications include data transmission with a power constraint and, more recently, data storage on flash memories with a constraint on memory cell wear. In the la
Externí odkaz:
http://arxiv.org/abs/2001.02748