Mar 3, 2023 � In this paper, we propose VPD (Visual Perception with a pre-trained Diffusion model), a new framework that exploits the semantic information of a pre-trained�...

Compared with other pre-training methods, we show that vision-language pre-trained diffusion models can be faster adapted to down- stream visual perception�...

VPD is a framework that leverages the high-level and low-level knowledge of a pre-trained text-to-image diffusion model to downstream visual perception tasks.

Compared with other pre-training methods, we show that vision-language pre-trained diffusion models can be faster adapted to downstream visual perception tasks�...

Compared with other pre-training methods, we show that vision-language pre-trained diffusion models can be faster adapted to down- stream visual perception�...

A new framework that exploits the semantic information of a pre-trained text-to-image diffusion model in visual perception tasks.

May 19, 2024 � In this video I review the VPD paper from ICCV2023 that proposes a method that uses the ...
Duration: 9:44
Posted: May 19, 2024

A straight way to utilize the pre-trained text-to-image diffusion models for downstream perception tasks is to finetune the denoising U-Net [20] to predict�...

Diffusion models (DMs) have become the new trend of generative models and have demonstrated a powerful ability of conditional synthesis.

May 19, 2024 � It proposes a way to use diffusion models as a backbone encoder for various visual perception tasks such as semantic segmentation and depth estimation.