2 citations · 6 across the 17 of their papers we have counts for
8 papers · 1 filter
CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up
Songhua Liu, Zhenxiong Tan, Xinchao Wang
Diffusion Transformers (DiT) have become a leading architecture in image generation. However, the quadratic complexity of attention mechanisms, which are responsible for modeling t…
MEMO: Memory-Guided Diffusion for Expressive Talking Video Generation
Longtao Zheng, Yifan Zhang, Hanzhong Guo +6
Recent advances in video diffusion models have unlocked new potential for realistic audio-driven talking video generation. However, achieving seamless audio-lip synchronization, ma…
OminiControl: Minimal and Universal Control for Diffusion Transformer
Zhenxiong Tan, Songhua Liu, Xingyi Yang +2
We present OminiControl, a novel approach that rethinks how image conditions are integrated into Diffusion Transformer (DiT) architectures. Current image conditioning methods eithe…
LinFusion: 1 GPU, 1 Minute, 16K Image
Songhua Liu, Weihao Yu, Zhenxiong Tan +1
Modern diffusion models, particularly those utilizing a Transformer-based UNet for denoising, rely heavily on self-attention operations to manage complex spatial relationships, thu…
LiteFocus: Accelerated Diffusion Inference for Long Audio Synthesis
Zhenxiong Tan, Xinyin Ma, Gongfan Fang +1
Latent diffusion models have shown promising results in audio generation, making notable advancements over traditional methods. However, their performance, while impressive with sh…
Video-Infinity: Distributed Long Video Generation
Zhenxiong Tan, Xingyi Yang, Songhua Liu +1
Diffusion models have recently achieved remarkable results for video generation. Despite the encouraging performances, the generated videos are typically constrained to a small num…
AsyncDiff: Parallelizing Diffusion Models by Asynchronous Denoising
Zigeng Chen, Xinyin Ma, Gongfan Fang +2
Diffusion models have garnered significant interest from the community for their great generative ability across various applications. However, their typical multi-step sequential-…
MindBridge: A Cross-Subject Brain Decoding Framework
Shizun Wang, Songhua Liu, Zhenxiong Tan +1
Brain decoding, a pivotal field in neuroscience, aims to reconstruct stimuli from acquired brain signals, primarily utilizing functional magnetic resonance imaging (fMRI). Currentl…