To control object reveals in AI video, use a picture-in-picture hack. Place an image of the target object (e.g., Beanie Babies) within the initial frame you upload for animation. The AI model will then use this reference to "outpaint" the scene, creating a seamless reveal of the desired object.

Related Insights

Advanced generative media workflows are not simple text-to-video prompts. Top customers chain an average of 14 different models for tasks like image generation, upscaling, and image-to-video transitions. This multi-model complexity is a key reason developers prefer open-source for its granular control over each step.

Instead of a complex 3D modeling process for Comet's onboarding animation, the designer used Perplexity Labs. By describing a "spinning orb" and providing a texture, she generated a 360-degree video that was cropped and shipped directly, showcasing how AI tools can quickly create high-fidelity, hacky production assets.

Create a hands-off content pipeline by combining two AI tools. Use ChatGPT with specific prompts to generate fully-fleshed-out video scripts. Then, instead of filming them yourself, paste those scripts directly into InVideo.ai to have the final video product generated automatically.

Successful AI video production doesn't jump from text to video. The optimal process involves scripting, using ChatGPT for a shot list, generating still images for each shot with tools like Rev, animating those images with models like VEO3, and finally, editing them together.

Most generative AI tools get users 80% of the way to their goal, but refining the final 20% is difficult without starting over. The key innovation of tools like AI video animator Waffer is allowing iterative, precise edits via text commands (e.g., "zoom in at 1.5 seconds"). This level of control is the next major step for creative AI tools.

Not all AI video models excel at the same tasks. For scenes requiring characters to speak realistically, Google's VEO3 is the superior choice due to its high-quality motion and lip-sync capabilities. For non-dialogue shots, other models like Kling or Luma Labs can be effective alternatives.

Instead of using generic stock footage, Roberto Nickson uses AI image and video tools like FreePik (Nano Banana) and Kling. This allows him to create perfectly contextual B-roll that is more visually compelling and directly relevant to his narrative, a practice he considers superior to stock libraries.

App developers can enhance their app's premium feel by animating static assets like logos or mascots. Midjourney, often known for image generation, has a feature that can animate an input image with a single click, creating looping videos perfect for splash screens or onboarding flows, adding life with minimal effort.

Avoid the "slot machine" approach of direct text-to-video. Instead, use image generation tools that offer multiple variations for each prompt. This allows you to conversationally refine scenes, select the best camera angles, and build out a shot sequence before moving to the animation phase.

When analyzing video, new generative models can create entirely new images that illustrate a described scene, rather than just pulling a direct screenshot. This allows AI to generate its own 'B-roll' or conceptual art that captures the essence of the source material.