First, if you haven't seen Thomas Blanchard's work — go fix that immediately: u/thomas__blanchard

He's a French visual alchemist who films macro footage of paint, oil, milk, honey, soap, and chemical crystallizations (potassium phosphate, sodium acetate) mixing on plates and petri dishes. 20x Vimeo Staff Pick. Genuinely one of the most hypnotic things you can watch. His latest project CRYSTALS was assembled from 150,000+ macro photographs of crystallization growth. The man is built different.

The core challenge

Thomas's work is 100% real physics at macro scale — chemical reactions, fluid dynamics, surface tension, Marangoni effect. The transitions are NOT cuts. They're continuous real-time transformations of matter. This is exactly the kind of content that breaks AI video models, because:

• No recognizable "objects" for the model to anchor on
• Pure texture + color + motion — all three changing simultaneously
• Transitions happen within the substance, not between shots
• Physics is non-Newtonian and weird

So what's the actual state of the art for generating this kind of content?

Approach 1: Seedance 2.0 — best for continuous abstract flow

Why it works: Seedance has genuinely strong emergent fluid behavior. If you give it a good first frame (or a real reference macro shot as Video1), it can extrapolate the motion reasonably.

The key prompt pattern:

 as the first frame.
Extreme macro shot of oil paint and milk mixing on a glass plate,
filmed from directly above. Vivid pigments — deep crimson, cobalt blue,
iridescent gold — blooming outward in slow organic tendrils.
Surface tension breaks create radial wave patterns. Tiny paint
spheres orbit larger formations. Camera completely static.
No camera movement whatsoever. Slow dreamlike motion, 24fps.

Tips:

• Lock the camera. Say "completely static camera" 2-3 times. The model wants to move the camera on abstract content and it destroys the macro illusion.
• Use a real macro still from your phone / stock as Image1 as first frame — it grounds the model in actual liquid texture. Without it, you get "paint splatter illustration" vibes, not real fluid.
• For the "planet balls" effect (paint in rapeseed oil) — describe them explicitly: "spherical paint droplets suspended in transparent oil medium, perfectly round, colors separating due to surface tension"
• 8-second clips work better than 15s for maintaining texture coherence. Stitch in Kling.

Weakness: Transitions between color zones tend to be mushy/dissolve-y rather than chemical-reaction-sharp. It doesn't know why the fluids are moving.

Approach 2: Kling 3.0 — best for first/last frame control + Luma Uni-1 for style transfer

The workflow:

1. Generate a strong keyframe in Midjourney or FLUX (macro oil/paint photography style — shoot your own is better)
2. Use Kling's Image-to-Video with first frame locked
3. Generate a second keyframe (different color state of the same "reaction")
4. Use Kling's first-frame + last-frame interpolation to get the transition

This is the closest you can get to Thomas's in-camera transitions without physically mixing paint.

Kling prompt for abstract liquid:

Extreme macro cinematography of acrylic paint mixing in milk.
The colors (ultramarine blue, cadmium yellow, alizarin crimson) are
slowly spiraling outward from a central disturbance point.
Surface of the liquid is reflective. Black background bleeds through
where fluids thin out. Completely static overhead camera.
Hypnotic slow motion. No people, no objects, pure fluid abstraction.

Uni-1 Modify trick: Take a real macro liquid photo → feed into Luma Uni-1 Modify Image with prompt "change color palette to [X], maintain all fluid textures and surface details exactly" → use that as keyframe input for Kling. Lets you color-grade the reference without losing the physical texture detail.

Approach 3: LTX Video — best for crystallization / growth patterns

LTX handles slow-growth and structural emergence better than the others. For Thomas's CRYSTALS-style content (potassium phosphate, ice dendrites, fractal growth):

Ultra-macro timelapse of crystal formation growing outward from
center point on dark glass surface. Needle-like transparent structures
branch into fractal patterns, each branch spawning smaller branches.
Illuminated from below with cool blue light. Black background.
The growth follows a radial pattern, filling frame edge to edge.
Slow, meditative pace — 1 second of real time shown over 5 seconds.
No camera movement.

Why LTX here: It handles "structural emergence" — something appearing from nothing — better than Seedance/Kling which prefer motion of existing objects. Crystal growth is fundamentally generative, which plays to LTX's strengths.

The problem: LTX still struggles with the micro-detail of actual crystalline structures. It goes abstract/painterly fast. Run multiple seeds (10+) and cherry-pick.

On transitions specifically

Thomas's transitions are mostly:

1. Bloom transitions — one color substance expanding into another (surface tension)
2. Veil/membrane — a thin fluid film splitting or merging
3. Orbit transitions — a paint sphere drifting across frame to become the new subject

For AI replication:

Option A: Use Seedance's /Video1 reference slot — feed in a real Thomas clip with face-blurred if needed (technically not needed for abstract content) with syntax completely reference /Video1's transition style and motion dynamics.

Option B: Kling Edit mode — start from a generated frame, describe the new color state, let Kling figure out the transition physics. Works surprisingly well when the color change is dramatic.

Option C: Generate transitions as separate clips, then use a subtle cross-dissolve in post at 8-12 frames. Thomas himself uses actual cuts occasionally — the "seamless" quality comes from compositional continuity, not always real continuous footage.

Honest assessment

None of these tools get you to Thomas Blanchard quality. He's shooting real physics with a macro lens in a 15m² studio and selecting <2% of his takes. The real texture of fluid dynamics at that scale — the wobble of a paint droplet, the Marangoni convection cells — is not something any current model generates correctly.

But you can get to "inspired by" territory that's genuinely beautiful on its own terms if you:

• Use real macro reference images as anchors (shoot your own on phone with macro lens attachment, ~$15)
• Keep camera static — this is non-negotiable
• Work in 8s clips and stitch
• Accept that you're making AI abstract video art, not a Thomas Blanchard simulation

What I'd love to know from this community:

• Has anyone had luck using ComfyUI + LTX for continuous abstract simulation? Specifically curious about multi-seed blending workflows
• Any experience with Runway's Gen-4 for this? I've been avoiding it but maybe it handles fluid physics better
• Anyone tried feeding actual fluid simulation renders (Houdini/Blender FLIP) as Video1 reference for texture overlay in Seedance?

Drop your approaches below. Credit Thomas Blanchard if you post results anywhere — the man spent 4 months and 150,000 photos on CRYSTALS. We're standing on the shoulders of an actual craftsman.

Hey pro-level folks — VFX / pipeline people specifically.

I'm building a workflow that mimics a real multi-camera film shoot of a car driving through a real intersection and turning from one street onto another. The goal isn't "AI-looking video" — it's spatially coherent, location-accurate footage from multiple angles, the same way you'd cover a car scene with:

• A ground-level tracking shot following the car
• A side-angle static from the corner
• A high oblique (simulated drone/crane)
• A cut to the opposite corner as the car exits frame

All of these need to feel like they were shot at the same real intersection. Not inspired by it — actually it.

Tool stack I'm working with:

• FLUX 2 Pro/Max — first frame / keyframe / environment image generation (HEX-locked to real location palette)
• Luma Uni-1 — Kontext-style image editing + realistic image anchoring from photo references (Create → Modify chain)
• Seedance 2.0 — final video generation with Video1 / Image1 reference system
• Claude — prompt engineering for all three models (structured JSON DNA-lock format for FLUX, role-labeled refs for Uni-1, time-segmented prompts for Seedance)
• NukeX — compositing
• Baselight — color grading

No characters. Pure location + one vehicle.

The core pipeline question

Think of it like real car shoot coverage:

Unit 1: Tracking shot — camera car follows the vehicle around the turn
Unit 2: Static corner — camera planted at the exit of the turn
Unit 3: Aerial — 45° oblique drone above the intersection
Unit 4: Opposite POV — looking back at where the car came from

Each of these is a separate Seedance generation. Each needs to feel like the same intersection in the same light at the same moment.

My current theory for location anchoring:

Real street photos (4-8 angles) + drone stills
        ↓
Uni-1 [Create] — generate photoreal environment keyframe per camera angle
        (using street photos as ENVIRONMENT refs, drone stills for aerial angles)
        ↓
Uni-1 [Modify] — lock car into each keyframe at correct position/scale for that angle
        ↓
FLUX 2 Pro — alternative path: HEX-locked environment keyframe per angle
        (5+ color zones locked to real location, ARRI Alexa 65 / 2.39:1 camera DNA)
        ↓
Seedance 2.0 — per-angle clip generation
        image_1 = Uni-1 or FLUX keyframe of that angle
        video_1 = face-blurred reference video from real location (same angle)
         as the first frame, u/Video1's camera movement and environment as reference
        ↓
NukeX — spatial comp, plate alignment, vehicle contact shadows
        ↓
Baselight — grade match to real location reference

Specific questions

1. Uni-1 vs FLUX for environment keyframes — which locks location better?

Uni-1's Create mode with IMAGE1 (ENVIRONMENT) + IMAGE2 (COMPOSITION) roles seems stronger for photorealism when working from real photo refs. FLUX 2 Pro gives me more predictable HEX palette control but hallucinates architecture more freely.

Anyone tested both as image_1 anchors going into Seedance? Which holds location geometry better through the video generation?

2. Reference injection cadence in Seedance — how often to re-anchor?

For a 4-angle sequence on the same intersection:

• Does each Seedance clip need its own angle-specific keyframe as image_1?
• Or can you use one establishing shot as a global environment anchor and trust Seedance to infer the correct geometry for other angles?

My assumption: you need a unique keyframe per angle — same intersection, camera repositioned, same lighting and palette. Is that correct?

3. Seedance slot logic for a pure vehicle shot (no characters)

Without characters there are no asset IDs needed. Current slot assignment I'm testing:

image_1 = Uni-1/FLUX keyframe — this camera angle
image_2 = car reference (specific model, color, exact spec)
image_3 = lighting/time-of-day reference (golden hour, shadow direction)
image_4 = empty
video_1 = real location reference clip, this angle (face-blurred)
video_2 = car motion reference (matching speed/direction)
asset_1–3 = empty

Does it make sense to use image_2 and image_3 as additional location refs from adjacent angles to give Seedance spatial context for the turn geometry? Or does that confuse the model?

4. The turn itself — spatial continuity across the cut

This is the hardest part. Unit 1 sees the car approach the corner. Unit 2 (static at exit) sees it complete the turn and accelerate away. These are two separate Seedance generations that need to feel spatially connected.

Options I'm testing:

• Last frame of Unit 1 → image_1 of Unit 2 (temporal handoff)
• Shared overhead aerial keyframe as a spatial map referenced in both clips
• Generate the aerial first, use a frame extract from it as the COMPOSITION reference in Uni-1 when building ground-level keyframes

Has anyone found a reliable method for spatial continuity across angle cuts that wasn't stitched together in comp?

5. Claude in the loop — structured prompt generation

Using Claude with custom skill files to generate:

• FLUX 2 Pro JSON blocks with per-zone HEX color assignment for environment keyframes
• Uni-1 multi-role prompts (ENVIRONMENT + COMPOSITION + LIGHTING per angle)
• Seedance time-segmented prompts with correct @ syntax per clip

The idea is to generate all prompts for all 4 angles in one structured Claude session, with shared location DNA (palette, light direction, time of day) locked across the entire batch. Anyone running a similar prompt-generation layer upstream of their ComfyUI workflow?

What I'd love to hear:

• Your asset injection strategy for multi-angle single-scene coverage
• Whether Uni-1's ENVIRONMENT role actually holds real architecture accurately enough to anchor Seedance
• Any ComfyUI graph patterns for this kind of angle-set batch generation
• How you handle the turn geometry problem in comp vs. at the generation stage

This is production-pipeline territory, not "make a cool AI video" territory. Looking for people who've actually pushed multi-angle location lock past the single-shot level. 👇