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Ahmed Doghri

physicsvideo

Five actual MP4 scenarios contain four planted physical faults. The benchmark finds all four with no false positive on the clean control.

physicsvideo generated film physical consistency test
physicsvideo working browser demo

Plausible Frames Can Make Impossible Motion

A generated clip may look sharp frame by frame while an object accelerates upward under gravity, teleports, disappears, or ignores a declared collision.

physicsvideo evaluates tracked trajectories with explicit tests for acceleration, displacement jumps, visibility gaps, and velocity reversal, then renders the scenarios to real MP4 files.

The Demo

Five scenarios include one clean control and four targeted faults. The benchmark detects all four planted failures and produces zero false positives, for 100% fixture accuracy.

This tests supplied tracks and declared events. General videos require reliable tracking, camera-motion compensation, depth, contact inference, and uncertainty-aware thresholds.

Research Basis

Recent benchmarks treat physical commonsense and temporal consistency as distinct requirements for modern video generation systems.

Read the PhyCoBench.

Tools Used

Python
OpenCV
Video Generation
Physical Consistency
MP4
Docker
GitHub Actions CI