It kept the subject and secondary pedestrians consistent through a full ~20-second continuous walking shot, with no ghosting or motion breakdown.
What was measured
Motion handling
Does quality degrade when the subject moves quickly, gestures, or leans?
decisive for this rankingtransformation
A video-background tool has to keep working when the subject moves; failure here means the core effect breaks down. (3 of 3 judges)
What was given, what came back
Test input: Busy Urban Street · video · group: remove-or-replace-video-backgrounds-using-ai
Input — what we sent
Busy Urban Street
A video of a person walking through a busy city street with multiple people, moving vehicles, and a visually complex urban background. It was used to stress segmentation and tracking under heavy background distraction and continuous motion.
Why this input is hard
- · Complex background segmentation
- · Handling background distractions
- · Subject tracking
- · Temporal consistency across frames
- · Edge accuracy during continuous movement
Output — unretouched
Also checked on this input — same tool, 3 other criteria
Edge quality✓ WorkedIt maintained clean cutout edges in the low-contrast night scene, with no halo or sky-bleed around the silhouette.Output resolution✗ FailedIt silently downgraded to 1080×1918 instead of true 4K, and the close crop looks soft rather than 4K-sharp.Temporal consistency✓ WorkedThe replacement background stayed steady despite continuous camera motion, with no visible flicker or warping across the clip.
Provenance
- Observation
- 5f180402-d5a5-4872-adad-33942d1ff44d
- Evidence run
- 10155228-7ce8-438a-a210-547331ef080b
- Study
- Remove or Replace Video Backgrounds Using AI
- Research task
- 86ba42c2d
- Tested at
- not recorded
- Source
- first-party
- Evidence state
- verified
- Proof shown
- input + output shown
- Cost / latency
- not captured
- Repeat run
- not captured
- Tester
- not captured
The last three rows are honest blanks, not placeholders — our capture has no field for them yet.
Query this
get_evidence({
tool: "invideo-ai",
scenario: "remove-or-replace-video-backgrounds-using-ai"
})MCP · mcp.aidemos.com/api/mcp
Free with attribution.
Same input, same check — 7 other tools
measured on Motion handling
Bria.ai✓ WorkedBoth pedestrians remained separately isolated while walking, so multi-subject motion did not cause subject loss.Cutout.Pro✓ WorkedKeeps a moving foreground pedestrian isolated while the background stays removed, and even a second person can appear as a separate cutout in one frame.Descript⚠ StruggledThe requested in-motion subjects are rendered more static and posed than the source’s forward-stride feel, so motion energy is flattened.Fotor✓ WorkedThe tool tracked 3–4 background pedestrians at once through a full 20-second continuous-motion clip without merging or dropping anyone.Kapwing⚠ StruggledAt several other points in the busy-street clip, incompletely erased gray blobs and leftover pedestrian traces lingered on the white background instead of being fully removed.Media.io✓ WorkedThe cutout held up as several people shifted position through the frame, including one person moving from center toward the right and others entering at the edges.Picsart✗ FailedIn a two-person moving street clip, the primary walker stayed isolated but the second pedestrian was erased entirely, indicating a single-subject lock-on in dynamic scenes.
This evidence is published in
Real inputs and real outputs, no retouching · every cell queryable via API & MCP · aidemos.com