Google’s research division is developing a neural network aimed at removing noise from photographs to elevate overall quality. A video demo showcases how the technology operates and the improvements it can deliver in challenging lighting conditions.
An AI powered tool named RawNeRF, which is part of the open source project MultiNeRF, has the capability to reconstruct scenes in low light by delivering strong noise suppression. This approach is particularly useful when a photo is captured at night and contains noticeable artifacts and grain.
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After processing: After processing
In addition, the neural network can generate three dimensional scenes from a sequence of standard images. A demonstration video illustrates this process and what the output looks like when the pipeline converts 2D imagery into a spatial model.
The MultiNeRF project makes its source code available on a public repository, inviting researchers to explore and contribute to the ongoing development.
Earlier reports also highlighted advances in neural networks that process collections of photos to produce new content and enhanced visuals, as shown by recent demonstrations tied to game and media production systems.
Attributions for the reported material are noted in industry coverage, reflecting ongoing interest in how neural networks handle image enhancement and 3D reconstruction tasks.