21 papers
Generative Refinement Networks for Visual Synthesis
Jian Han, Jinlai Liu, Jiahuan Wang +2
While diffusion models dominate the field of visual generation, they are computationally inefficient, applying a uniform computational effort regardless of different complexity. In…
Dual-End Consistency Model
Linwei Dong, Ruoyu Guo, Ge Bai +3
The slow iterative sampling nature remains a major bottleneck for the practical deployment of diffusion and flow-based generative models. While consistency models (CMs) represent a…
Bernini: Latent Semantic Planning for Video Diffusion
Bernini Team, Chenchen Liu, Junyi Chen +9
Multimodal large language models (MLLMs) and diffusion models have each reached remarkable maturity: MLLMs excel at reasoning over heterogeneous multimodal inputs with strong seman…
Guiding Distribution Matching Distillation with Gradient-Based Reinforcement Learning
Linwei Dong, Ruoyu Guo, Ge Bai +3
Diffusion distillation, exemplified by Distribution Matching Distillation (DMD), has shown great promise in few-step generation but often sacrifices quality for sampling speed. Whi…
BindWeave: Subject-Consistent Video Generation via Cross-Modal Integration
Zhaoyang Li, Dongjun Qian, Kai Su +6
Diffusion Transformer has shown remarkable abilities in generating high-fidelity videos, delivering visually coherent frames and rich details over extended durations. However, exis…
ALIVE: Animate Your World with Lifelike Audio-Video Generation
Ying Guo, Qijun Gan, Yifu Zhang +13
Video generation is rapidly evolving towards unified audio-video generation. In this paper, we present ALIVE, a generation model that adapts a pretrained Text-to-Video (T2V) model…