Published: 2025-11-15 03:02:23 UTC
To fix morphing object glitches in AI-generated video you must isolate the faulty frames and selectively re-render them with a model that offers stronger temporal consistency, then reintegrate the corrected clips into the final edit. Coca-Cola’s 2025 AI holiday ads highlighted how trucks can suddenly gain wheels or change shape when generative models drift frame to frame, eroding brand polish and viewer trust. In this guide we’ll explain why these glitches occur, how to diagnose them, proven techniques to repair or prevent them, and where purpose-built platforms like Truepix AI can streamline the process.
Most text-to-video systems render footage one short clip at a time. Without an explicit memory of previous frames, objects can "drift," causing wheels to disappear, truck cabins to warp, or motion paths to veer unexpectedly—a phenomenon researchers label temporal drift.
High-profile campaigns such as Coca-Cola’s 2025 remake of its 1995 "Holidays Are Coming" spot used OpenAI’s Sora, Google’s Veo 3, and Luma AI. Viewers quickly noticed trucks changing shape and even pointing toward crowds. Business Insider called this "one of the biggest shortcomings of generative video models."
Because inconsistent objects instantly signal "AI," brands risk decreased trust and craftsmanship scores when these errors remain visible.
1. Export a high-resolution draft and scrub slowly through each shot. Pause whenever an object appears to stretch, flicker, or change dimensions.
2. Create a shot log noting timecodes, type of glitch (e.g., missing wheel, warped chassis), and the original prompt or seed if available.
3. Tag severity. Minor misalignments may be masked in post; major geometry shifts usually require re-generation.
Regenerating an entire 60-second spot can waste GPU budget and introduce new errors. A more surgical approach is to re-render only the flawed clips.
Truepix AI’s ADS Agent, for example, supplies marketers with a supplementary file listing the URL of every generated clip plus the exact text prompt. If a truck’s wheel vanishes at second 12, you can copy that URL, tweak the prompt ("maintain all four wheels"), and regenerate just that segment—saving hours compared with starting over.
Not all models handle object permanence equally. Some prioritise cinematic motion but sacrifice geometry stability. Others, often trained on longer sequence data, maintain better frame-to-frame coherence.
Platforms with intelligent routing can help. Truepix AI’s Intelligent Model Selection engine automatically evaluates your task and—if a draft shows morphing wheels—can shift to a model with stronger temporal metrics before you hit "render" again. You can also override the choice manually if you have a preferred model for object permanence.
For teams working directly with open-source models, experiment with settings such as lower motion weight, higher geometric consistency loss, or extended latent conditioning to curb drift.
1. Use explicit language: "red Coca-Cola delivery truck, SAME shape and four wheels in every frame" can nudge models toward stability.
2. Provide reference images or a short still sequence of the hero object; many systems let you feed these as conditioning inputs.
3. Lock camera motion when possible. Static or slow pans reduce the visual complexity the model must track.
4. Split complex scenes: generate the truck and the background separately, then composite, so each model focuses on fewer elements.
These best practices not only fix current glitches but also represent the best way to ensure temporal consistency in AI video ads moving forward.
After re-inserting corrected clips, run a second QC pass with fresh eyes or an automated frame-difference tool to catch residual flicker.
Minor alignment hiccups can often be solved with motion-tracking, warping, or masking in Adobe After Effects or DaVinci Resolve.
Testing firms like DAIVID have shown that even small visual inconsistencies raise audience distrust scores; a final polish cycle is therefore essential.
When timelines are tight, tools that streamline selective re-renders, maintain prompt history, and offer automatic model routing give marketers a competitive edge.
Truepix AI bundles all three: URL-level clip access, prompt recall, and an auto-optimiser for model choice. While OpenAI’s Sora or Google’s Veo offer impressive raw generation, they currently require more manual juggling to correct object-consistency issues.
Whichever platform you pick, insist on features that help maintain object permanence across AI video frames and make iterative workflows painless.
Generative video models often render short clips without a persistent memory of previous frames, leading to temporal drift where geometry like a truck’s chassis or wheels morphs between frames.
Yes. Export the glitchy segment’s prompt and seed, adjust the wording to reinforce object permanence, and regenerate only that clip; platforms such as Truepix AI automate this selective re-rendering by providing URLs and prompts for each shot.
Look for models trained on long-sequence data, lower motion weights, higher geometric consistency loss parameters, and enable reference-image conditioning where available.
Truepix AI’s Intelligent Model Selection engine automatically picks a model with stronger coherence metrics when it detects consistency issues, and its ADS Agent lets you regenerate only the flawed clips using the original prompts.
Post tools can mask minor flicker or alignment errors, but significant geometry changes usually require re-generation to avoid noticeable artifacts.
Maintaining consistent objects—whether a Coca-Cola truck or a brand mascot—is now the litmus test for professional AI video. By diagnosing errors early, selectively regenerating problem clips, choosing models tuned for temporal accuracy, and reinforcing prompts with references, creative teams can overcome today’s generative limitations. Tools like Truepix AI, with built-in prompt recall and intelligent model routing, further shorten the path from glitch-ridden draft to polished, on-brand footage.