Execution Evidence · nmVR Camera

Adaptive Camera Control

Neural vs Cinemachine-like baseline for fast sports tracking and VR horizon stabilization
The neural camera stays steadier through sharp turns, frame drops, and head bobble while the classical baseline reacts later and swings wider

Neural Cinemachine-like Connecting...
Sports - Top View

Fast Sports Tracking

White is the player. Red and blue are the camera aim points trying to keep up.

Cinemachine-like Neural Target

The red baseline follows well in calm motion, but it swings wider when the frame rate drops. The blue neural camera predicts where motion is going next, so aiming stays tighter and easier to read during sprints and direction changes.

Why it matters: in sports and action games, steadier tracking means clearer target framing, less camera whip, and more room to push speed without making the scene feel unstable.

VR - Horizon Stabilization

VR Horizon Stability

White is raw head bobble. Red and blue are the remaining horizon shake after each method tries to cancel it.

Cinemachine-like Neural Target / Raw Motion

Here, the best result is the flattest line. White is the original head motion. Red and blue show how much shake is left after correction. If blue is flatter than red, the neural controller is doing a better job stabilizing the horizon.

Why it matters: a more stable horizon can reduce discomfort, keep motion easier to read, and make VR feel safer during movement.

Cinemachine-like Error: - px

Overshoot: - px

Jitter: -

FPS: -

Neural Error: - px

Overshoot: - px

Jitter: -

VR Residual: -