Zobrazeno 1 - 10
of 105
pro vyhledávání: '"Colburn, Alex"'
Autor:
Guo, Pengsheng, Hao, Hans, Caccavale, Adam, Ren, Zhongzheng, Zhang, Edward, Shan, Qi, Sankar, Aditya, Schwing, Alexander G., Colburn, Alex, Ma, Fangchang
In the realm of text-to-3D generation, utilizing 2D diffusion models through score distillation sampling (SDS) frequently leads to issues such as blurred appearances and multi-faced geometry, primarily due to the intrinsically noisy nature of the SDS
Externí odkaz:
http://arxiv.org/abs/2312.02189
Autor:
Zhao, Xiaoming, Colburn, Alex, Ma, Fangchang, Bautista, Miguel Angel, Susskind, Joshua M., Schwing, Alexander G.
Rendering scenes observed in a monocular video from novel viewpoints is a challenging problem. For static scenes the community has studied both scene-specific optimization techniques, which optimize on every test scene, and generalized techniques, wh
Externí odkaz:
http://arxiv.org/abs/2310.08587
Autor:
Ziwen, Chen, Patnaik, Kaushik, Zhai, Shuangfei, Wan, Alvin, Ren, Zhile, Schwing, Alex, Colburn, Alex, Fuxin, Li
Real world images often have highly imbalanced content density. Some areas are very uniform, e.g., large patches of blue sky, while other areas are scattered with many small objects. Yet, the commonly used successive grid downsampling strategy in con
Externí odkaz:
http://arxiv.org/abs/2304.12406
Autor:
Stier, Noah, Ranjan, Anurag, Colburn, Alex, Yan, Yajie, Yang, Liang, Ma, Fangchang, Angles, Baptiste
Recent works on 3D reconstruction from posed images have demonstrated that direct inference of scene-level 3D geometry without test-time optimization is feasible using deep neural networks, showing remarkable promise and high efficiency. However, the
Externí odkaz:
http://arxiv.org/abs/2304.01480
Dense 3D reconstruction from RGB images traditionally assumes static camera pose estimates. This assumption has endured, even as recent works have increasingly focused on real-time methods for mobile devices. However, the assumption of a fixed pose f
Externí odkaz:
http://arxiv.org/abs/2304.00054
Autor:
Zhao, Xiaoming, Ma, Fangchang, Güera, David, Ren, Zhile, Schwing, Alexander G., Colburn, Alex
What is really needed to make an existing 2D GAN 3D-aware? To answer this question, we modify a classical GAN, i.e., StyleGANv2, as little as possible. We find that only two modifications are absolutely necessary: 1) a multiplane image style generato
Externí odkaz:
http://arxiv.org/abs/2207.10642
Autor:
Guo, Pengsheng, Bautista, Miguel Angel, Colburn, Alex, Yang, Liang, Ulbricht, Daniel, Susskind, Joshua M., Shan, Qi
We study the problem of novel view synthesis from sparse source observations of a scene comprised of 3D objects. We propose a simple yet effective approach that is neither continuous nor implicit, challenging recent trends on view synthesis. Our appr
Externí odkaz:
http://arxiv.org/abs/2107.05775
Annual luminance maps provide meaningful evaluations for occupants' visual comfort, preferences, and perception. However, acquiring long-term luminance maps require labor-intensive and time-consuming simulations or impracticable long-term field measu
Externí odkaz:
http://arxiv.org/abs/2009.09928
Autor:
Dupont, Emilien, Bautista, Miguel Angel, Colburn, Alex, Sankar, Aditya, Guestrin, Carlos, Susskind, Josh, Shan, Qi
We propose a framework for learning neural scene representations directly from images, without 3D supervision. Our key insight is that 3D structure can be imposed by ensuring that the learned representation transforms like a real 3D scene. Specifical
Externí odkaz:
http://arxiv.org/abs/2006.07630
We present DeepExpr, a novel expression transfer system from humans to multiple stylized characters via deep learning. We developed : 1) a data-driven perceptual model of facial expressions, 2) a novel stylized character data set with cardinal expres
Externí odkaz:
http://arxiv.org/abs/1911.08591