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Found 4 papers, 3 papers with code
LFSRDiff: Light Field Image Super-Resolution via Diffusion Models
Despite this complexity, mainstream LF image SR methods typically adopt a deterministic approach, generating only a single output supervised by pixel-wise loss functions.
OccCasNet: Occlusion-aware Cascade Cost Volume for Light Field Depth Estimation
To address this issue and achieve a better trade-off between accuracy and efficiency, we propose an occlusion-aware cascade cost volume for LF depth (disparity) estimation.
Learning Sub-Pixel Disparity Distribution for Light Field Depth Estimation
However, the disparity map is only a sub-space projection (i. e., an expectation) of the disparity distribution, which is essential for models to learn.
Soft policy optimization using dual-track advantage estimator
In reinforcement learning (RL), we always expect the agent to explore as many states as possible in the initial stage of training and exploit the explored information in the subsequent stage to discover the most returnable trajectory.
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