r/NeuralCinema

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. 👇