Immersity AI is a 2D-to-3D conversion platform from Leia Inc. that adds depth, stereo effects, and camera motion to existing images and videos. Instead of asking AI to invent a new scene, you give Immersity finished media and let its Neural Depth Engine interpret the spatial relationships inside it. The result can be anything from a moving social post to stereoscopic content for XR displays such as Apple Vision Pro and Meta Quest.

That makes Immersity more of a conversion and presentation tool than a traditional generative image editor. Its strongest use case is taking content you already like and making it feel dimensional without rebuilding the scene manually in 3D software.

Immersive Motion is probably the easiest place to understand what Immersity does.

Upload a still image, choose a camera movement, and the system turns the flat picture into an animated clip with simulated depth and perspective. You can create effects such as zooming, panning, or shifting the viewpoint without manually separating foreground and background layers.

This works particularly well with images that already contain obvious depth cues. A portrait in front of a distant landscape, a street extending toward the horizon, layered artwork, architectural photography, or a product surrounded by foreground objects gives the system more spatial information to work with.

It is less about generating dramatic cinematic movement and more about giving static media a convincing sense of dimensional motion.

Immersity can also turn 2D images into stereoscopic 3D rather than animated 2D clips.

Supported viewing options include parallel and cross-eyed stereo formats, anaglyph images, spatial-photo formats for compatible Apple devices, and Leia's own LIF format. These outputs are intended for devices capable of presenting separate views to each eye, including XR hardware and compatible 3D displays.

That makes the tool useful for someone building spatial photo collections or preparing existing artwork for newer display formats.

Video conversion is where the technology faces a harder problem.

Immersity analyzes the footage and generates depth information across the sequence, allowing ordinary 2D footage to be exported as stereoscopic video. It also supports spatial video intended for Apple Vision Pro, alongside other 3D formats for compatible displays.

The appeal is obvious for older footage. You don't need to have filmed with a stereoscopic camera to experiment with spatial presentation later.

There is an important limitation, though. Immersity's FAQ notes that video frames can introduce artifacts around edges, transparent objects, and reflections. Because depth is being estimated across changing frames, temporal inconsistencies can also appear.

A clean landscape shot may convert more convincingly than fast footage full of hair, glass, smoke, reflections, or objects repeatedly crossing in front of one another.

One of Immersity's less flashy but more useful features is standalone depth-map generation.

Instead of only exporting the final effect, users can obtain the depth information used to construct it. That gives experienced creators more room to continue working in other software.

Depth maps can help with foreground and background separation, depth-aware compositing, parallax effects, and workflows where the automatic animation isn't the desired final result. Immersity specifically positions this feature as a way to refine work in third-party applications.

For professional users, this may matter more than the preset motion effects.

Immersity now has two noticeably different workflows.

That split makes sense. Mobile is better suited to turning a few photos into something visually interesting without learning 3D tools. The web app is where Immersity becomes more relevant to designers, spatial-content creators, and professional media workflows.

A more specialized feature is Apple Music Album Motion.

Artists and labels can upload square artwork, apply Immersity's 3D motion treatment, and export versions formatted around Apple's Album Motion requirements. Immersity prepares both 1:1 and 3:4 versions and handles presentation details such as the blurred background used for the taller layout.

It is a narrow feature, but a practical one. Instead of rebuilding an album cover as a layered motion project, an artist can start from the finished artwork and add restrained depth movement.

Immersity AI fits photographers who want dimensional versions of existing images, social creators turning still photos into motion clips, musicians preparing animated album artwork, XR creators converting older 2D media, and designers who need AI-generated depth maps for further editing.

Travel photography is another natural match. Landscapes, architecture, interiors, and street scenes already contain strong spatial layers, which gives the depth engine more information to interpret.

It is less appropriate when the real goal is changing the image itself. Immersity is not a substitute for Photoshop, a text-to-image model, or a full 3D modeling package.

• Hidden depth still has to be inferred: Depth estimation can only infer information that isn't present in the original image. Hidden surfaces remain unknown, and complicated boundaries can produce visible distortions.
• Transparency and reflections are difficult: Transparency and reflections are difficult areas, while video can introduce frame-to-frame depth changes. Abstract artwork can also produce unpredictable results because the system may interpret shapes differently from the creator's intended spatial structure.
• Stereo output requires compatible hardware: Full stereoscopic output also needs the right display hardware to appreciate properly. Immersive Motion can be viewed on an ordinary screen, but genuine stereo images and videos require compatible XR, 3D, or Immersity-enabled displays.
• Source quality matters: So the source image matters. Strong subject separation and obvious foreground, middle-ground, and background structure usually give the technology a better foundation.