132 citations · 325 across the 36 of their papers we have counts for
7 papers · 1 filter
High Quality Human Image Animation using Regional Supervision and Motion Blur Condition
Zhongcong Xu, Chaoyue Song, Guoxian Song +8
Recent advances in video diffusion models have enabled realistic and controllable human image animation with temporal coherence. Although generating reasonable results, existing me…
Empowering Visual Creativity: A Vision-Language Assistant to Image Editing Recommendations
Tiancheng Shen, Jun Hao Liew, Long Mai +3
Advances in text-based image generation and editing have revolutionized content creation, enabling users to create impressive content from imaginative text prompts. However, existi…
DiG: Scalable and Efficient Diffusion Models with Gated Linear Attention
Lianghui Zhu, Zilong Huang, Bencheng Liao +4
Diffusion models with large-scale pre-training have achieved significant success in the field of visual content generation, particularly exemplified by Diffusion Transformers (DiT)…
ClassDiffusion: More Aligned Personalization Tuning with Explicit Class Guidance
Jiannan Huang, Jun Hao Liew, Hanshu Yan +4
Recent text-to-image customization works have proven successful in generating images of given concepts by fine-tuning diffusion models on a few examples. However, tuning-based meth…
LightningDrag: Lightning Fast and Accurate Drag-based Image Editing Emerging from Videos
Yujun Shi, Jun Hao Liew, Hanshu Yan +2
Accuracy and speed are critical in image editing tasks. Pan et al. introduced a drag-based image editing framework that achieves pixel-level control using Generative Adversarial Ne…
PeRFlow: Piecewise Rectified Flow as Universal Plug-and-Play Accelerator
Hanshu Yan, Xingchao Liu, Jiachun Pan +3
We present Piecewise Rectified Flow (PeRFlow), a flow-based method for accelerating diffusion models. PeRFlow divides the sampling process of generative flows into several time win…