Sony · Filed Apr 15, 2025 · Published Nov 5, 2026

Sony Files Patent for Matching Up 3D Characters Using Flat Snapshots of Each One

Sony has a patent application for lining up two 3D characters by taking a flat picture of each and letting an AI find the matching spots. The twist is the trip back: every match is traced onto the exact spot on the 3D model.

Facial expressions from video transferred through rough digital shapes onto a final animated face. Drawing from patent filing US 2026/0350921 A1.
Facial expressions from video transferred through rough digital shapes onto a final animated face.
See all 31 drawings from this filing ↓
Publication number US 2026/0350921 A1 US20260350921A1
Applicant Sony Interactive Entertainment Inc.
Filing date Apr 15, 2025
Publication date Nov 5, 2026
Inventors Chockalingam Ravi Sundaram
US classification 345/420
Examiner SAMS, MICHELLE L (Art Unit 2611)
Status when we published Waiting for an examiner (Sep 30, 2025)
Document 20 claims

What Sony's flat-snapshot matching actually does

Ever tried to match a rough sketch of a face with a detailed portrait of the same person? You'd look for the eyes, the mouth, the chin, and tell yourself "these go together." Computers find that surprisingly hard when both faces are 3D models built from thousands of tiny points.

Sony's patent application sidesteps the problem. Instead of comparing the two 3D models directly, it takes a flat snapshot of each, like photographing two statues. An AI trained on ordinary flat pictures, where training material is plentiful, spots which parts match, say left eye to left eye. The system then traces each match on the picture back to the exact spot on the 3D model.

Why bother? The filing says artists now do this matching by hand when they turn video into 3D animation. Automating it could let a simple animated face drive a much more detailed one.

From the filing · CLAIM 1
… forwarding, to a featuring matching neural network, a network input comprising: (i) the two-dimensional source image, and (ii) the two-dimensional target image …

Translation: The system feeds both flat pictures into an artificial intelligence network to compare them.

How Sony turns 2D matches back into 3D points

The core idea is a round trip: 3D to 2D and back to 3D. The system receives two 3D meshes (digital shapes built from a net of tiny triangles), a source and a target. In the filing's main example the target is the more detailed one, and both are faces.

It renders each mesh into an ordinary 2D image, using a virtual camera and a virtual light, much like a studio photo. Both images go into a feature matching neural network (an AI model that finds the same feature in two pictures). The network returns pairs of matching spots, such as eye to eye, and can add a confidence score for each pair.

Then comes the step the claim hinges on: inverse rasterizing. While rendering, the system records which triangle each pixel came from. Run backward, that record turns every matched pixel into points on the 3D model.

The filing also describes optional extras:

  • Filters that throw out likely mismatches before the trip back to 3D
  • Repeating the process from several sides (front, back, top and so on) so hidden spots still get matched

Why this could speed up 3D animation work

For animation teams, this targets a slow, manual job. The filing lists uses such as turning old hand-drawn cartoons into 3D, turning 2D game cutscenes into 3D assets, converting older 2D content for virtual reality, and converting videos shot on a phone. If you've ever wondered why remaking old animation in 3D is so costly, hand-matching points between models is part of the answer.

This patent covers only the matching stage of a three-part pipeline. The other two stages build a rough 3D animation from video and then transfer that motion onto the detailed model. The filing notes that matching happens once per pair of models, which is how it describes keeping live video conversion faster than the frame rate.

Sony's 23rd filing we've tracked in AI simulation since May follows one cutting cloud-game lag and one converting video to 3D.

Editorial take

Claim 1 is short, and that makes it wide. It asks for two 3D models, a flat picture of each, an AI that pairs up spots between the pictures, and a step that carries those pairs back onto the models.

The claim never mentions faces, animation, video, or one model being more detailed than the other. Those details show up only in later claims and the description. Claim 2 leaves the AI wide open too, listing five network families. As written, the claim reaches any tool that matches two 3D models through this snapshot, match and trace-back loop, whatever AI sits in the middle.

The idea itself is sensible. Matching spots in flat pictures is an area with plenty of training material, according to the filing, so the claim borrows that strength for 3D work. Whether it matters outside animation depends on what examiners make of that breadth.

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The drawings

31 drawing sheets from US 2026/0350921 A1 · click any drawing to enlarge

How flat video turns into a moving 3D digital double, drawing sheet 1 from US 2026/0350921 A1
Sheet 1 How flat video turns into a moving 3D digital double
Matching facial expressions from video onto a new character model, drawing sheet 2 from US 2026/0350921 A1
Sheet 2 Matching facial expressions from video onto a new character model
Front and side wireframe views of the original face, drawing sheet 3 from US 2026/0350921 A1
Sheet 3 Front and side wireframe views of the original face
Rear and alternate angles of the original wireframe face, drawing sheet 4 from US 2026/0350921 A1
Sheet 4 Rear and alternate angles of the original wireframe face
Front and side views of the new character head, drawing sheet 5 from US 2026/0350921 A1
Sheet 5 Front and side views of the new character head
Back and opposite profile angles of the target character head, drawing sheet 6 from US 2026/0350921 A1
Sheet 6 Back and opposite profile angles of the target character head
Steps for linking two different digital faces to transfer animation, drawing sheet 7 from US 2026/0350921 A1
Sheet 7 Steps for linking two different digital faces to transfer animation
A simplified sequence for moving performance capture between models, drawing sheet 8 from US 2026/0350921 A1
Sheet 8 A simplified sequence for moving performance capture between models
Show the other 23 sheets
Turning raw video into a moving 3D digital model, drawing sheet 9 from US 2026/0350921 A1
Sheet 9 Turning raw video into a moving 3D digital model
Steps for rebuilding face movements inside a 3D digital model, drawing sheet 10 from US 2026/0350921 A1
Sheet 10 Steps for rebuilding face movements inside a 3D digital model
Matching facial features across two 3D models using flat snapshots, drawing sheet 11 from US 2026/0350921 A1
Sheet 11 Matching facial features across two 3D models using flat snapshots
Matching points on two 3D models using their photos, drawing sheet 12 from US 2026/0350921 A1
Sheet 12 Matching points on two 3D models using their photos
Converting a 3D shape into a flat 2D picture, drawing sheet 13 from US 2026/0350921 A1
Sheet 13 Converting a 3D shape into a flat 2D picture
Projecting matched photo spots back onto the 3D model, drawing sheet 14 from US 2026/0350921 A1
Sheet 14 Projecting matched photo spots back onto the 3D model
Projecting a 3D surface point onto a screen pixel, drawing sheet 15 from US 2026/0350921 A1
Sheet 15 Projecting a 3D surface point onto a screen pixel
Calculating how a 3D shape appears as a 2D image, drawing sheet 16 from US 2026/0350921 A1
Sheet 16 Calculating how a 3D shape appears as a 2D image
Converting flat picture landmarks into 3D facial coordinates, drawing sheet 17 from US 2026/0350921 A1
Sheet 17 Converting flat picture landmarks into 3D facial coordinates
Matching up corresponding facial landmarks on two flat pictures, drawing sheet 18 from US 2026/0350921 A1
Sheet 18 Matching up corresponding facial landmarks on two flat pictures
Paired landmark points positioned across both 3D face models, drawing sheet 19 from US 2026/0350921 A1
Sheet 19 Paired landmark points positioned across both 3D face models
Mathematical calculation for transferring motion across models, drawing sheet 20 from US 2026/0350921 A1
Sheet 20 Mathematical calculation for transferring motion across models
First half of calculating movement transfer between two faces, drawing sheet 21 from US 2026/0350921 A1
Sheet 21 First half of calculating movement transfer between two faces
Finishing calculation steps to build the final animated target face, drawing sheet 22 from US 2026/0350921 A1
Sheet 22 Finishing calculation steps to build the final animated target face
Real-time system streaming webcam video directly into 3D avatar motion, drawing sheet 23 from US 2026/0350921 A1
Sheet 23 Real-time system streaming webcam video directly into 3D avatar motion
Steps for continuously animating an avatar from live video frames, drawing sheet 24 from US 2026/0350921 A1
Sheet 24 Steps for continuously animating an avatar from live video frames
Training the AI to turn photos into 3D face shapes, drawing sheet 25 from US 2026/0350921 A1
Sheet 25 Training the AI to turn photos into 3D face shapes
Steps for teaching the AI using single photos, drawing sheet 26 from US 2026/0350921 A1
Sheet 26 Steps for teaching the AI using single photos
How the AI learns to recreate moving 3D face animations, drawing sheet 27 from US 2026/0350921 A1
Sheet 27 How the AI learns to recreate moving 3D face animations
Updating the AI to reconstruct facial movement from video, drawing sheet 28 from US 2026/0350921 A1
Sheet 28 Updating the AI to reconstruct facial movement from video
Teaching the AI to connect facial features between different photos, drawing sheet 29 from US 2026/0350921 A1
Sheet 29 Teaching the AI to connect facial features between different photos
Comparing paired image landmarks to improve the matching AI, drawing sheet 30 from US 2026/0350921 A1
Sheet 30 Comparing paired image landmarks to improve the matching AI
Gaming gear and cloud servers that run the animation tools, drawing sheet 31 from US 2026/0350921 A1
Sheet 31 Gaming gear and cloud servers that run the animation tools
Browse all the drawings 31 drawing sheets
Patent filing page

Source. Full patent text and figures from the official USPTO publication PDF.
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