u/artanimore — reddlx

Tested Seedance 2.5 with a few T2V experiments.

For text-to-video, the overall quality is definitely impressive.
It handles materials surprisingly well too.

But once you move beyond realistic visuals into things like LEGO, origami, or other stylized transformations, the model has to interpret a lot more on its own.

That’s where the structure, assembly logic, and small details can start drifting away from what you actually intended.

My takeaway:

For this kind of work, it’s probably better to design the reference image first, then animate from that reference, rather than relying on pure T2V from the beginning.

T2V quality is getting much better, but the more specific and stylized the idea is, the more important a strong visual reference becomes.

instagram.com

u/artanimore — 6 days ago

▲ 18 r/film_ai+1 crossposts

Hard match cut test — 30 cuts in 53 seconds, all landing on muzzle flashes

I wanted to see how far hard match cuts could go in AI video,
so I built a gun kata action sequence as a test.
The thing that actually worked wasn't making two frames look alike.
It was where I cut. Cutting after an action completes always showed the seam.
Cutting mid-motion — while the arm is still swinging, while the body is still falling — the seam disappeared.
Every transition here lands on either a muzzle flash blowing out the frame or a wall of thrown water. Neither is subtle, but that's the point: the eye reads it as impact, not as a cut.
Two other things I got wrong first: - Writing "3D rendered" in the prompt made the engine render 3D graphics. What I actually wanted was "the space is three-dimensional." Splitting those two ideas apart is what finally gave the shots depth. - The curved bullet shot didn't read until I made his arm swing through a full arc before firing. Without a visible cause, a curving projectile just looks like a glitch. Midjourney for the first frames, Seedance for motion, Suno for the score. Happy to share the full prompt structure if anyone wants it.

u/artanimore — 7 days ago

▲ 2 r/aivideos

I tested 17 image references in one 30-second Seedance 2.5 generation.

The goal was to pair eight masks with eight environments and make each pair transform at the same moment.

What I found:

• Upload order influenced the sequence more strongly than the order written in the prompt.
• Mask and environment changes needed to be written in the same sentence and time segment.
• “A changes into B” often produced a dissolve.
• A visible transformation boundary created a more physical environmental change.
• Landscape references needed to be redefined as a surrounding 3D space.
• Persistent elements and replacement areas had to be separated explicitly.

The final result maintained all eight mask–environment pairs across the 30-second sequence.

The biggest takeaway: with complex multi-reference generation, structure mattered more than prompt length.

u/artanimore — 12 days ago

▲ 12 r/aivideos

Tested Seedance 2.5's reference image limit — the spec says 50, the platform capped me at 30

I designed 45 creatures in Midjourney for a single
continuous 30-second jungle chase, planning to use the full reference capacity.

Two things I didn't expect:

The platform I used caps uploads at 30, not 50.
Model spec ≠ what you can actually submit.
Audio reference caps at 30.2 seconds. Cost me a failed run before I read the error properly. Ended up running 15.

Creatures with similar silhouettes bled into each other — you don't lose one, you lose both.

Distinctiveness turned out to be load-bearing, not a style choice. Prompt structure and the creature sheets in the comments if anyone wants them.

u/artanimore — 13 days ago