Both pedestrians remained separately isolated while walking, so multi-subject motion did not cause subject loss.
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
Also checked on this input — same tool, 4 other criteria
Edge quality⚠ StruggledThe cutouts are dim and partially soft-edged, with semi-transparent edge fringing and residue in gaps that should read as pure black.Hair and fine detail⚠ StruggledSnow-on-subject detail was mostly removed, and a thin phone cord/earbud wire was softened further until it was barely visible.Hair and fine detail⚠ StruggledThe busy-street cutout loses fine detail such as fingers and backpack strap edges, which become blobbed or softened after removal.Output resolution✓ WorkedThe output preserved the source resolution exactly at 1080×1920, with no downscaling.
Provenance
- Observation
- 3fdb7ce8-2f77-457f-83c9-ae067f7d42d6
- 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: "bria-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
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.InVideo AI✓ WorkedIt kept the subject and secondary pedestrians consistent through a full ~20-second continuous walking shot, with no ghosting or motion breakdown.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