4 Major Upgrades to Seedance Pro Video Generation Model Technology

Seedance Pro is a high-performance and efficient AI video generation model that has achieved technological breakthroughs in command following, movement and rationality, and picture quality, enabling high-quality video generation capabilities for multiple scenes and complex subjects.

Architecture Design

Seedance Pro is optimized using the RLHF learning method, a reinforcement learning method from human feedback, significantly improving motion naturalness, structural coherence, and visual fidelity. Furthermore, a multi-stage systematic optimization approach achieves a 10x inference speedup, generating a 5-second 1080p video in just 41.4 seconds on an NVIDIA-L20 graphics card.

Data Processing

Seedance Pro builds a large-scale, high-quality video dataset through multi-stage data preprocessing. This includes acquiring diverse video footage, compliance screening, shot segmentation, and visual correction. This data preprocessing is combined with high-quality manually annotated data to train the model and automatically generate subtitles and other video data content.

Model Training

Seedance Pro employs multiple training strategies, including pre-training, continuous training (CT), supervised fine-tuning (SFT), and realignment with human feedback (RLHF), to gradually improve model performance, including resolution, frame rate, image generation capabilities, output bias, and motion naturalness.

Inference Optimization

Seedance Pro uses diffusion distillation to reduce the number of function evaluations (NFEs) required for generation while maintaining model performance. Inference efficiency is further improved through technologies such as kernel fusion, quantization, sparsification, and parallelization strategies.