This is an AI video generation comparison for
image-to-video 
prompt:
A man runs towards the camera in a park (or forest). As the character runs past, the camera performs a fast whip pan to follow, blurring the entire scene into horizontal streaks. The blur acts as a transition: when the whip pan stops, the scene is now a city and the man is running away from the camera on a busy sidewalk....
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Tested: November 8, 2025
Nice. Only there's a contagion effect - other peole are also running.
Tested: November 8, 2025
Great execution of the whip pan.
Tested: November 8, 2025
Kling's whip pan tends to be quicker than other models', brief motion blur behind the subject and the new scene is revealed. Looks more like a dynamic tracking shot...
Tested: November 8, 2025
Execution is similar to Kling's here, not so much whip-panning as tracking the guy as he turns.
Does the character clearly run toward the camera, maintaining consistent forward motion?
Is the camera stable and properly tracking the running character before the whip pan begins?
When the whip pan starts, does the entire scene blur horizontally with smooth streaks (no jittering or tearing)?
Does the whip pan speed feel natural, neither too slow nor instantaneous?
Does the blur fully obscure the forest before the city scene appears?
When the whip pan stops, is the new scene (city) clearly visible and distinct from the forest?
Is the character’s position consistent—same outfit and direction, now running away from the camera in the city?
Are city details (sidewalk, people, vehicles) sharp and populated enough to feel busy?
Does motion blur cleanly resolve into focus once the camera stops moving?
Check out the results from GROK (Grok Imagine v0.9) vs Wan (Online Platform) (Wan2.5 Preview) vs Freepik (Hailuo 2.3 Fast) vs Freepik (Kling 2.5 Turbo Standard) vs PixVerse (PixVerse V5) for similar or identical prompts side-by-side.
