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Suttisak Wizadwongsa

4 accepted papers

2024

Diffusion Sampling with Momentum for Mitigating Divergence Artifacts

ICLR 2024poster

Despite the remarkable success of diffusion models in image generation, slow sampling remains a persistent issue. To accelerate the sampling process, prior studies have reformulated diffusion sampling as an ODE/SDE and introduced higher-order numerical methods. However, these methods often produce d…

2023

Accelerating Guided Diffusion Sampling with Splitting Numerical Methods

ICLR 2023poster

Guided diffusion is a technique for conditioning the output of a diffusion model at sampling time without retraining the network for each specific task. However, one drawback of diffusion models, whether they are guided or unguided, is their slow sampling process. Recent techniques can accelerate u…

2022

Diffusion Autoencoders: Toward a Meaningful and Decodable Representation

CVPR 2022oral

Diffusion probabilistic models (DPMs) have achieved remarkable quality in image generation that rivals GANs'. But unlike GANs, DPMs use a set of latent variables that lack semantic meaning and cannot serve as a useful representation for other tasks. This paper explores the possibility of using DPMs…

Cited by 456PDFcodeScholar
2021

NeX: Real-Time View Synthesis With Neural Basis Expansion

CVPR 2021poster

We present NeX, a new approach to novel view synthesis based on enhancements of multiplane image (MPI) that can reproduce next-level view-dependent effects--in real time. Unlike traditional MPI that uses a set of simple RGBa planes, our technique models view-dependent effects by instead parameterizi…

Cited by 320PDFcodeScholar