2D-to-3D conversion adds the binocular disparity depth cue to digital images perceived by the brain, thus, if done properly, greatly improving the immersive effect while viewing stereo video in comparison to 2D video. However, in order to be thus successful, the conversion should be done with sufficient accuracy and correctness: the quality of the original 2D images should not deteriorate, and the introduced disparity cue should not contradict to other cues used by the brain for depth perception. If done properly and thoroughly, the conversion produces stereo video of similar quality to "native" stereo video which is shot in stereo and accurately adjusted and aligned in post-production.
Without respect to particular algorithms, all conversion workflows should solve the following tasks: 
Allocation of “depth budget” – defining the range of permitted disparity or depth, what depth value corresponds to the screen position (so-called “convergence point” position), the permitted distance ranges for out-of-the-screen effects and behind-the-screen background objects. If an object in stereo pair is in exactly the same spot for both eyes, then it will appear on the screen surface and it will be in zero parallax. Objects in front of the screen are said to be in negative parallax, and background imagery behind the screen is in positive parallax. There are the corresponding negative or positive offsets in object positions for left and right eye images.
Control of comfortable disparity depending on scene type and motion – too big parallax or conflicting depth cues may cause eye-strain and nausea effects
Filling of uncovered areas – left or right view images show a scene from a different angle, and parts of objects or entire objects covered by the foreground in the original 2D image should become visible in a stereo pair. Sometimes the background surfaces are known or can be estimated, so they should be used for filling uncovered areas. Otherwise the unknown areas should be guesstimated and painted in, since the exact reconstruction is not possible.
High quality conversion methods should also deal with many typical problems including:
Fuzzy semitransparent object borders – such as hair, fur, foreground out-of-focus objects, thin objects
Film grain (real or artificial) and similar noise effects
Scenes with fast erratic motion
Small particles – rain, snow, explosions and so on.