Google Veo3.1 Reference To Video

Google Veo3.1 Reference To Video

Playground

Google Veo3.1 Reference-to-Video performs image-to-video generation that preserves a specific subject’s appearance and identity from provided reference images, enabling consistent character or product motion across frames. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Veo 3.1 Reference-to-Video brings static images to life by combining visual reference consistency with cinematic motion generation. Powered by Google DeepMind’s next-generation Veo 3.1 architecture, this model transforms up to three reference images into coherent 5-second videos with smooth motion, accurate visual alignment, and synchronized native audio.

🌟 Key Features

🧠 Multi-Image Reference Support

• Accepts up to three reference images to define the subject, environment, or style.
• Maintains consistent identity, lighting, and appearance across frames.
• Ideal for animating people, objects, or scenes with reliable fidelity.

🎬 Cinematic Video Generation

• Produces 5-second motion clips at 1080p or 720p resolution.
• Adds camera dynamics such as panning, zooming, or subtle perspective drift.
• Supports synchronized audio generation, matching dialogue or ambient context.

💡 Smart Prompt Adherence

• Interprets both text instructions and visual cues for precise motion storytelling.
• Automatically harmonizes character interactions, props, and backgrounds.

⚙️ Capabilities

• Input:

• Up to 3 reference images (JPEG / PNG / WEBP)

• Text prompt describing motion, action, and scene context

• Output:

• 8-second MP4 video (720p or 1080p)

• Optional synchronized audio

• Negative Prompt (optional):

• Exclude unwanted artifacts or elements (e.g., “no text”, “no flicker”).

• Seed (optional):

• Reproduce specific results for consistent creative control.

💰 Pricing

✅ Commercial use allowed

🧩 How to Use

1. Upload up to 3 reference images — define the subject, object, or visual style.
2. Write a text prompt — describe the action, setting, and camera motion.
3. (Optional) Add a negative prompt to remove unwanted details.
4. Choose resolution (720p or 1080p).
5. (Optional) Enable audio generation for synchronized sound.
6. Click Run to generate your 5-second cinematic video.

💡 Best Practices

• Use clear, well-lit reference images with similar styles and proportions.
• Keep prompts concise but specific (e.g., “The man in image 1 waves to the penguins in image 2 under bright sunlight”).
• Avoid overly complex scenarios with many characters or fast movement.
• Enable audio for more immersive storytelling results.

📝 Notes

• Ensure uploaded images are valid and accessible URLs or uploaded locally.
• If the output looks unstable, reduce reference count or simplify the prompt.
• Follow Google’s content safety rules; modify the prompt if flagged.
• For best performance, prefer portrait-oriented subjects and balanced lighting.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result

set -euo pipefail

export WAVESPEED_API_KEY="your-api-key"

REQUEST_BODY=$(cat <<'JSON'
{
  "prompt": "A cinematic ocean wave at sunrise, highly detailed",
  "images": [
    "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
  ],
  "resolution": "1080p",
  "generate_audio": true
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/google/veo3.1/reference-to-video" \
  -H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  -H "Content-Type: application/json" \
  -d "${REQUEST_BODY}")

TASK=$(printf '%s' "${SUBMIT_RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "${TASK}" | jq -r '.id // empty')
if [ -z "${PREDICTION_ID}" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(printf '%s' "${TASK}" | jq -r '.urls.get // empty')
if [ -z "${RESULT_URL}" ]; then RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"; fi

# 2. Poll until the prediction finishes.
while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body \
    "${RESULT_URL}" \
    -H "Authorization: Bearer ${WAVESPEED_API_KEY}")
  RESULT=$(printf '%s' "${RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
  STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')

  case "${STATUS}" in
    completed) printf '%s\n' "${RESULT}" | jq '.outputs'; break ;;
    failed|cancelled|timeout) printf '%s\n' "${RESULT}" | jq . >&2; exit 1 ;;
    created|processing) sleep 2 ;;
    *) printf 'Unexpected status: %s
' "${STATUS}" >&2; exit 1 ;;
  esac
done

Parameters

Task Submission Parameters

Request Parameters

Response Parameters

Result Request Parameters

Result Response Parameters