Parakeet Pretends to Sleep While Hiding Glowing Phone

A cinematic 8K live-action style clip of a small rosy-faced parakeet in a dim bedroom at night, scrolling a glowing smartphone under a thick white quilt with extremely shallow depth of field. When footsteps approach, the bird hides the phone, shuts its eyes, and fakes sleep as a blurred owner silhouette peeks in from the door.

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GENEL | AIを用いた動画制作 @genel_ai ·
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Prompt

シネマティックな8K実写スタイル動画。深夜の薄暗い寝室。極端に浅い被写界深度(F1.2)で、手前のインコにのみ完璧にピントが合い、背景は強くボケている。画面内にUIやテキストは一切なし。 主人公は淡い水色の羽毛、白い顔、鮮やかなピンクの丸いチークを持つ小さなコザクラインコ。葉っぱ模様のある分厚い白い掛け布団に潜っている。 インコは布団の中から左足を出し、目の前に置かれた発光するスマホの画面を小さな爪でスワイプしている。スマホの光が顔を青白く照らす。 突然、近づく足音を察知してインコはピタリと硬直する。目は見開かれ、警戒する。 インコは素早くスマホを体と布団の奥深くに押し込んで光を完全に隠し、目を固く閉じて布団に深く沈み込み、完璧な「寝たふり」をする。 直後、大きくボケた背景領域で木製のドアが開き、廊下からオレンジ色の暖かい光が差し込む。強くボケて顔が判別できない飼い主のシルエットが部屋を覗き込む。手前のインコはピントが合ったまま、微動だにせず息を潜めている。
? How to use this prompt ▾
  1. Copy the prompt using the green "Copy prompt" button above.
  2. Open your model — launch Seedance 2.0 on its official interface.
  3. Paste & generate — keep the verbatim prompt text for best adherence. Set aspect ratio to 16:9 and clip duration to 10s.

What makes this prompt work

Every insight below is verified against benchmark generation parameters, not asserted. How our prompt engineering benchmarks work →

CAMERA
"close-up" is a core cinematic camera technique for establishing spatial immersion and subject framing.
LIGHTING
"silhouette, low-key" establishes luminance depth, volumetric shadow falloff, and tonal contrast across the generation.
MOOD
"tense, cinematic" — Mood and aesthetic tone are explicitly directed to maintain emotional consistency throughout the scene.
DURATION
At 10s, this clip is optimized for high temporal coherence and fluid, realistic motion physics.
MODEL
Seedance 2.0 (ByteDance) provides the underlying diffusion and motion architecture. Camera, lighting and duration cues transfer across models — what differs is how literally each model interprets motion.
PROMPT LANGUAGE
The prompt is written in Chinese. This library keeps every prompt in its original language rather than translating it — the exact words are what was conditioned during generation.
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