Video depixelation: what AI can and cannot restore
Video depixelation uses a model to estimate detail in a pixelated region. A mosaic-reduced video can look more coherent, but that appearance does not establish that the original hidden detail has been recovered. Heavy mosaic, blur and compression remove different kinds of information.
Mosaic, blur and compression are different problems
Mosaic replaces fine detail with blocks. Blur spreads detail across nearby pixels. Compression artifacts can create block edges, ringing and banding. A tool designed for mosaic restoration may not solve all of these problems equally well.
Increasing output resolution alone does not restore lost information. Upscaling changes the size of the image; reconstruction estimates what might fit the remaining visual evidence.
Does uncensoring recover the original video?
The words uncensor and mosaic removal are often used for AI reconstruction. They should not be read as a promise of an authentic uncensored original. The restored output contains model estimates and can introduce details that were never present in the source.
Evaluate the output as an edited reconstruction. Do not use inferred faces, text or other details as proof of identity, events or original content. The homepage comparison is a sample illustration, not a quality guarantee for an uploaded file.
A repeatable quality check
Compare at the same resolution and timestamp. View normal-speed motion as well as individual frames. Pay attention to temporal consistency, preserved edges, audio synchronization and unwanted changes outside the target region.
Large mosaic blocks, small subjects, repeated compression and fast movement can make results less reliable. A preview from your own source is more informative than a promotional before-and-after image.