6 papers
Seedance 2.0: Advancing Video Generation for World Complexity
Team Seedance, De Chen, Liyang Chen +168
Seedance 2.0 is a new native multi-modal audio-video generation model, officially released in China in early February 2026. Compared with its predecessors, Seedance 1.0 and 1.5 Pro…
Seedance 1.5 pro: A Native Audio-Visual Joint Generation Foundation Model
Team Seedance, Heyi Chen, Siyan Chen +194
Recent strides in video generation have paved the way for unified audio-visual generation. In this work, we present Seedance 1.5 pro, a foundational model engineered specifically f…
Hyper-Bagel: A Unified Acceleration Framework for Multimodal Understanding and Generation
Yanzuo Lu, Xin Xia, Manlin Zhang +4
Unified multimodal models have recently attracted considerable attention for their remarkable abilities in jointly understanding and generating diverse content. However, as context…
Seaweed-7B: Cost-Effective Training of Video Generation Foundation Model
Team Seawead, Ceyuan Yang, Zhijie Lin +52
This technical report presents a cost-efficient strategy for training a video generation foundation model. We present a mid-sized research model with approximately 7 billion parame…
UGC: Unified GAN Compression for Efficient Image-to-Image Translation
Yuxi Ren, Jie Wu, Peng Zhang +6
Recent years have witnessed the prevailing progress of Generative Adversarial Networks (GANs) in image-to-image translation. However, the success of these GAN models hinges on pond…
DiffusionEngine: Diffusion Model is Scalable Data Engine for Object Detection
Manlin Zhang, Jie Wu, Yuxi Ren +7
Data is the cornerstone of deep learning. This paper reveals that the recently developed Diffusion Model is a scalable data engine for object detection. Existing methods for scalin…