BYTEDANCE

Bytedance Image-to-Video Pro v1.5 powered by Seedance 1.5 is an advanced AI model designed to generate cinematic videos with synchronized audio from a combination of image and text inputs. This model is particularly suited for users seeking to animate still images into high-quality motion sequences that include dialogue, ambient sound, and nuanced camera movement. By leveraging a start frame (and optionally an end frame), users can directly define the initial and final compositions, enabling precise control over the visual and narrative flow of the video.

Seedance 1.5 Pro stands out as an image-to-video model by allowing users to upload a high-quality image to set the opening composition, lighting, subject, and style. For even greater creative control, an end frame can be provided, enabling the model to generate seamless and lifelike motion that transitions organically from start to finish. The model is not designed for text-to-video generation but excels when users require precise animation starting and ending at specific visuals.

Key features include:

• Start Frame Conditioning: The generated video inherits the subject, pose, lighting, color grade, and environment from an uploaded start frame. This ensures that the animated content closely matches the initial vision defined by the user.
• End Frame Conditioning (Optional): By uploading an optional end frame, users can dictate exactly where the video should culminate. The model synthesizes the motion and transformation between frames, delivering a shot that lands precisely on the end frame's composition.
• Native Audio Generation: Seedance 1.5 Pro produces synchronized dialogue, sound effects, and ambient audio, ensuring lip movements are accurately aligned with speech. Audio is output at 48 kHz AAC, and can be enabled or disabled as needed.
• Cinematic Camera Work: The model supports a range of camera operations—such as pan, tilt, zoom, dolly, orbit, and tracking shots—that can be described in the text prompt, offering comprehensive control over the cinematic feel of the output.
• Character Consistency: Subjects introduced in the start frame remain visually consistent throughout the generated video, maintaining their facial features, clothing, and emotional expression.
• High Resolution: Videos can be generated at up to 1080p resolution with smooth temporal coherence, supporting aspect ratios including 21:9, 16:9, 4:3, 1:1, 3:4, and 9:16.

The model accepts common image formats (jpg, jpeg, png, webp, gif, avif) for both start and end frames, and generates MP4 (H.264) video output. Video lengths can be customized between 4 and 12 seconds, with 5 seconds as the default duration. Users can select output resolutions of 480p, 720p, or 1080p, where 480p is optimized for quick iteration, and higher resolutions yield higher final quality.

The model's API supports additional configuration options:

• camera_fixed: Lock the camera in place for a tripod-like shot.
• aspect_ratio: Multiple options, with 16:9 as default.
• enable_safety_checker: Activate a safety filter if desired.
• generate_audio: Toggle audio generation.
• seed: Set for reproducibility or leave as random.

Ideal use cases, as documented, include:

• Photo animation: Bringing static images, such as portraits or product photos, to life with realistic motion and sound.
• Character animation: Turning single frames or concept art into emotive performances with accurate lip-sync.
• Product reveals: Coordinating smooth animated transitions between hero shots and packaging visuals.
• Scene transitions: Creating precise animations between defined compositions for advertisements, trailers, or music videos.
• Storyboard-to-video: Converting illustrated frames into motion tests with sound.
• Social content: Animating memes, portraits, or fan art into shareable video clips.
• Virtual avatars: Producing talking-head videos from a single headshot.

Prompting strategies are highlighted: the prompt should focus on events occurring between the frames, such as action, dialogue (enclosed in quotes for clarity), emotions, and camera moves. The start frame defines the scene, so prompts should guide motion and audio primarily. For talking heads, dialogue and the intended emotion can be explicitly stated in the prompt. The model’s motion is generated in latent space rather than simple interpolation, resulting in natural physics and camera movements.

Best practices mentioned include maintaining aspect ratio and style consistency between start and end frames for smooth transitions, and using the same subject in both frames for coherence. Limitations and considerations noted are the support for videos up to 12 seconds, maximum resolution of 1080p, and the need for start frame (and optionally end frame) images to direct animation effectively.

The output includes mixed dialogue, foley, and score in the generated video, and the exported format is MP4 encoded with H.264. The model is suitable for both creative and commercial projects, as commercial use is explicitly supported.