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Product Videos: Bring Product Images to Life ​

An ordinary product photo, after the two steps of "repaint product image → image-to-video," becomes a dynamic showcase ready for direct ad placement. This page walks you through the full AI product video pipeline using the official template templates-photo_to_product_vid.

When to Use This ​

  • Your detail pages need dynamic displays, but you have no studio-shoot budget or photography team.
  • You need to quickly produce multiple versions of video assets for social media and feed ads.
  • You already have real photos, or the product mockup generated on the previous page, and want to upgrade it to "studio-grade look + camera movement."
  • Not suitable for: videos featuring real people on camera or voiceover explanations—those are jobs for audio-driven digital humans.

Preparation ​

  1. First read the prerequisite page Wan2.2 14B Image-to-Video: Bring Photos to Life and install the image-to-video models.
  2. Load the official template templates/templates-photo_to_product_vid.json in ComfyUI.
  3. The template's first step uses ByteDanceSeedreamNode (located in comfy_api_nodes; service and key requirements depend on your actual environment), with the model seedream-4-5-251128 (Seedream 4.5).
  4. Limited VRAM? For the video step you can switch to Wan2.2 5B, which can run text-to-video and image-to-video locally for free with just 8GB of VRAM.

Follow Along: A 3-Step Workflow ​

Step 1: Repaint the Product Image with Seedream 4.5 ​

LoadImage loads the product photo and connects it to the image input of ByteDanceSeedreamNode. Write the prompt following the template's structure: subject and angle (e.g., "white Adidas Samba sneaker, three-quarter side view"), lighting (cool-toned hard light, floor glow), background (light silver-gray gradient to deep charcoal), composition (generous negative space, f/2.8 shallow depth of field).

Choose a resolution of 1664x2496 (2:3) and fix the seed (the template uses 555) for reproducibility. Connect a SaveImage first to save a static version for backup.

Step 2: Use Image-to-Video to Animate the Product ​

Feed the output image from step 1 into the image-to-video model, and describe the camera movement in the prompt. The latter half of the template actually consists of three MinimaxHailuoVideoNode nodes; connect the repainted product image to each node's first_frame_image input to generate three shots respectively—a push-in close-up, a sweep from heel to toe, and a 360° rotation showcase—at a resolution of 1080P; whether this node works directly also depends on your actual environment.

To run locally, you can switch to Wan2.2 14B I2V (configured per the prerequisite tutorial); if VRAM is tight, switch to Wan2.2 5B. Keep the camera movement moderate to prevent the product's structure from drifting.

Step 3: Export and Check the Final AI Product Video ​

The video is output through the SaveVideo node; check the duration, resolution, format, and encoding against the ad platform's requirements. If anything falls short, go back to the corresponding node, adjust, and rerun.

Checkpoints ​

  • Product image: verify the logo, structure, and textures haven't been altered by the repaint—Seedream does a full-image repaint, not a partial replacement.
  • Video: the first frame should match the product image; motion should look natural, with no tearing or flickering.
  • Consistency: the product's appearance must stay uniform across multiple versions of AI product video assets; fixing the seed helps.
  • Delivery: in the template, all SaveVideo parameters except the output path are auto; the actual format and encoding depend on the run. Confirm the platform can use the file directly before launch, and if not, transcode it with an external tool.

Boundaries and Next Steps ​

Boundaries:

  • Due to image-to-video model limitations, each clip has a limited duration; longer videos need to be generated in segments and stitched together.
  • Full-image repainting alters product details; use with caution for categories demanding extremely high consistency (jewelry engravings, serial numbers).
  • For real-person explanations requiring lip sync, use Wan2.2 S2V audio-driven digital humans instead.

Next steps: