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Alexander William Bergman

3 accepted papers

2024

Phased Consistency Models

NeurIPS 2024poster

Consistency Models (CMs) have made significant progress in accelerating the generation of diffusion models. However, their application to high-resolution, text-conditioned image generation in the latent space remains unsatisfactory. In this paper, we identify three key flaws in the current design of…

2022

Generative Neural Articulated Radiance Fields

NeurIPS 2022accept

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 radiance fields of existing frameworks are not dir…

Cited by 119SourcePDFScholar
2021

Fast Training of Neural Lumigraph Representations using Meta Learning

NeurIPS 2021poster

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 arbitrary views. These representations, however, are ext…

Cited by 43SourcePDFScholar