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Found 3 papers, 2 papers with code
Eta Inversion: Designing an Optimal Eta Function for Diffusion-based Real Image Editing
A commonly adopted strategy for editing real images involves inverting the diffusion process to obtain a noisy representation of the original image, which is then denoised to achieve the desired edits.
Focus on defocus: bridging the synthetic to real domain gap for depth estimation
We are able to train our model completely on synthetic data and directly apply it to a wide range of real-world images.
Ranked #1 on
Depth Estimation
on NYU-Depth V2
(RMSE metric)
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