The warm lantern-lit alley does not wrap light onto the subjects: jacket edges still read as flat daylight with no warm rim light.

⚠ Struggled🧾 artifact-verifiedinput + output shownTest date not recordedDescript
What was measured
Lighting adaptation

Does the replaced background look naturally lit relative to the subject, or obviously composited?

decisive for this rankingtransformation

If the replaced background does not match the subject’s lighting, the composite looks fake, so this is central to replacement quality. (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

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
image
Provenance
Observation
87e47faa-5505-4f29-95c7-726fa54b39c2
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: "descript",
  scenario: "remove-or-replace-video-backgrounds-using-ai"
})
MCP · mcp.aidemos.com/api/mcp
Free with attribution.
Same input, same check — 1 other tool
measured on Lighting adaptation
Real inputs and real outputs, no retouching · every cell queryable via API & MCP · aidemos.com