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Devindelarocka
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Cinematic Video Prompt
Aspect Ratio: 16:9 horizontal
Style: Photorealistic, raw found-footage aesthetic
Camera: First-person perspective (FPV), selfie-style, low angle looking up at the character
Device Simulation: iPhone handheld, slight shake for realism
Scene Concept
Setting:
A lively beach party at sunset in Maui. Golden light reflects off the ocean, tiki torches flicker in the background, and reggae music drifts from a nearby beach bar.
People are laughing in the distance, surfboards stacked against a palm tree, and the faint sound of waves crashing adds depth.
Character:
A Grizzly Bear with a surfer vibe: bright floral Hawaiian shirt, colorful surfer shorts, mirrored sunglasses.
He’s holding a half-empty coconut drink with a tiny umbrella and a slice of pineapple.
Camera Movement:
Starts with the camera held low, angled upward toward the bear’s face.
Slight wobble as if the person filming is tipsy.
Occasional lens flare from the sunset for realism.
Expression Progression (8 seconds):
Curious – Bear leans in, squints at the camera, tilts his head.
Drunk/Intoxicated – He sways, grins lazily, tongue slightly out, sunglasses slipping.
Wide-eyed Panic – Suddenly startled by a crab crawling on his foot.
Surprised & Dumbfounded – Mouth agape, sunglasses slide down his nose, coconut spills slightly.
Dialogue (Lip-Synced, Jamaican Reggae Accent, No Subtitles):
Bear:
“Ey mon… you ever seen a bear surf? Ha! Dis coconut talkin’ louder than me head, mon… Whoa—what’s dat?! Crab attack! Jah bless, dis beach is wild!”
Soundscape:
Ambient reggae beats in the background.
Ocean waves, distant laughter, and a sudden “snap” sound when the crab appears.
Bear’s voice is deep, rhythmic, and playful with exaggerated Jamaican inflection.
Inference Scaling
Implementation of scaling method during inferencing inspaired by Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps. Spend more computational resources to get better results. Use it by specifying the sampling option.
num_subtree=3
num_scaling_steps=5
num_noise=1
time=16min
num_subtree=7
num_scaling_steps=8
num_noise=1
time=1h