5 papers
Towards Robust Sequential Decomposition for Complex Image Editing
Zilai Zeng, Mingdeng Cao, Zijie Li +5
Recent advances in visual generative models have enabled high-fidelity image editing guided by human instructions. However, these models often struggle with complex instructions in…
MMCORE: MultiModal COnnection with Representation Aligned Latent Embeddings
Zijie Li, Yichun Shi, Jingxiang Sun +8
We present MMCORE, a unified framework designed for multimodal image generation and editing. MMCORE leverages a pre-trained Vision-Language Model (VLM) to predict semantic visual e…
Seedance 1.0: Exploring the Boundaries of Video Generation Models
Yu Gao, Haoyuan Guo, Tuyen Hoang +41
Notable breakthroughs in diffusion modeling have propelled rapid improvements in video generation, yet current foundational model still face critical challenges in simultaneously b…
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…
Learning Feature-Preserving Portrait Editing from Generated Pairs
Bowei Chen, Tiancheng Zhi, Peihao Zhu +3
Portrait editing is challenging for existing techniques due to difficulties in preserving subject features like identity. In this paper, we propose a training-based method leveragi…