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Found 3 papers, 2 papers with code
Elucidating the Exposure Bias in Diffusion Models
In this paper, we systematically investigate the exposure bias problem in diffusion models by first analytically modelling the sampling distribution, based on which we then attribute the prediction error at each sampling step as the root cause of the exposure bias issue.
Ranked #9 on
Image Generation
on CIFAR-10
Input Perturbation Reduces Exposure Bias in Diffusion Models
Denoising Diffusion Probabilistic Models have shown an impressive generation quality, although their long sampling chain leads to high computational costs.
Ranked #1 on
Image Generation
on FFHQ 128 x 128
SeeFar: Vehicle Speed Estimation and Flow Analysis from a Moving UAV
In this paper, we introduce SeeFar to achieve vehicle speed estimation and traffic flow analysis based on YOLOv5 and DeepSORT from a moving drone.
