Zobrazeno 1 - 10
of 515
pro vyhledávání: '"EVANS, ALEX"'
Autor:
Smith, Brenden, Baker, Dallin, Chase, Clayton, Barney, Myles, Parker, Kaden, Allred, Makenna, Hu, Peter, Evans, Alex, Fulda, Nancy
Large Language Models (LLMs) have an unrivaled and invaluable ability to "align" their output to a diverse range of human preferences, by mirroring them in the text they generate. The internal characteristics of such models, however, remain largely o
Externí odkaz:
http://arxiv.org/abs/2407.03621
The development of human-robot collaboration has the ability to improve manufacturing system performance by leveraging the unique strengths of both humans and robots. On the shop floor, human operators contribute with their adaptability and flexibili
Externí odkaz:
http://arxiv.org/abs/2406.01915
Autor:
Takikawa, Towaki, Müller, Thomas, Nimier-David, Merlin, Evans, Alex, Fidler, Sanja, Jacobson, Alec, Keller, Alexander
Neural graphics primitives are faster and achieve higher quality when their neural networks are augmented by spatial data structures that hold trainable features arranged in a grid. However, existing feature grids either come with a large memory foot
Externí odkaz:
http://arxiv.org/abs/2312.17241
Constant function market makers (CFMMs) are the most popular type of decentralized trading venue for cryptocurrency tokens. In this paper, we give a very general geometric framework (or 'axioms') which encompass and generalize many of the known resul
Externí odkaz:
http://arxiv.org/abs/2308.08066
Autor:
Li, Zhaoshuo, Müller, Thomas, Evans, Alex, Taylor, Russell H., Unberath, Mathias, Liu, Ming-Yu, Lin, Chen-Hsuan
Neural surface reconstruction has been shown to be powerful for recovering dense 3D surfaces via image-based neural rendering. However, current methods struggle to recover detailed structures of real-world scenes. To address the issue, we present Neu
Externí odkaz:
http://arxiv.org/abs/2306.03092
Autor:
Zeltner, Tizian, Rousselle, Fabrice, Weidlich, Andrea, Clarberg, Petrik, Novák, Jan, Bitterli, Benedikt, Evans, Alex, Davidovič, Tomáš, Kallweit, Simon, Lefohn, Aaron
Publikováno v:
ACM Trans. Graph. 43, 3, Article 33 (June 2024), 17 pages
We present a complete system for real-time rendering of scenes with complex appearance previously reserved for offline use. This is achieved with a combination of algorithmic and system level innovations. Our appearance model utilizes learned hierarc
Externí odkaz:
http://arxiv.org/abs/2305.02678
Autor:
Wen, Bowen, Tremblay, Jonathan, Blukis, Valts, Tyree, Stephen, Muller, Thomas, Evans, Alex, Fox, Dieter, Kautz, Jan, Birchfield, Stan
We present a near real-time method for 6-DoF tracking of an unknown object from a monocular RGBD video sequence, while simultaneously performing neural 3D reconstruction of the object. Our method works for arbitrary rigid objects, even when visual te
Externí odkaz:
http://arxiv.org/abs/2303.14158
In this paper, we introduce a family of games called concave pro-rata games. In such a game, players place their assets into a pool, and the pool pays out some concave function of all assets placed into it. Each player then receives a pro-rata share
Externí odkaz:
http://arxiv.org/abs/2302.02126
Autor:
Lin, Yunzhi, Müller, Thomas, Tremblay, Jonathan, Wen, Bowen, Tyree, Stephen, Evans, Alex, Vela, Patricio A., Birchfield, Stan
We present a parallelized optimization method based on fast Neural Radiance Fields (NeRF) for estimating 6-DoF pose of a camera with respect to an object or scene. Given a single observed RGB image of the target, we can predict the translation and ro
Externí odkaz:
http://arxiv.org/abs/2210.10108
We consider a continuous-time financial market with no arbitrage and no transactions costs. In this setting, we introduce two types of perpetual contracts, one in which the payoff to the long side is a fixed function of the underlyers and the long si
Externí odkaz:
http://arxiv.org/abs/2209.03307