Skip to content

🔥🔥[∆-DiT] ∆-DiT: A Training-Free Acceleration Method Tailored for Diffusion Transformers #21

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
DefTruth merged 1 commit into from
Dec 27, 2024
Merged

🔥🔥[∆-DiT] ∆-DiT: A Training-Free Acceleration Method Tailored for Diffusion Transformers #21

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
3 changes: 2 additions & 1 deletion README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -76,7 +76,8 @@
|2024.07| 🔥🔥[**Faster I2V Generation**] Faster Image2Video Generation: A Closer Look at CLIP Image Embedding’s Impact on Spatio-Temporal Cross-Attentions(@Ashkan Taghipour etc)|[[pdf]](https://arxiv.org/pdf/2407.19205) |⚠️|⭐️⭐️ |
|2024.04| 🔥🔥[**T-GATE V1**] Cross-Attention Makes Inference Cumbersome in Text-to-Image Diffusion Models(@Wentian Zhang etc)|[[pdf]](https://arxiv.org/pdf/2404.02747v1) | [[T-GATE]](https://github.com/HaozheLiu-ST/T-GATE) ![](https://img.shields.io/github/stars/HaozheLiu-ST/T-GATE.svg?style=social)|⭐️⭐️ |
|2024.04| 🔥🔥[**T-GATE V2**] Faster Diffusion via Temporal Attention Decomposition(@Haozhe Liu etc)|[[pdf]](https://arxiv.org/pdf/2404.02747v2) | [[T-GATE]](https://github.com/HaozheLiu-ST/T-GATE) ![](https://img.shields.io/github/stars/HaozheLiu-ST/T-GATE.svg?style=social)|⭐️⭐️ |
|2024.06| 🔥[**DiTFastAttn**] DiTFastAttn: Attention Compression for Diffusion Transformer Models(@Zhihang Yuan etc)|[[pdf]](https://arxiv.org/pdf/2406.08552) | [[DiTFastAttn]](https://github.com/thu-nics/DiTFastAttn) ![](https://img.shields.io/github/stars/thu-nics/DiTFastAttn.svg?style=social)|⭐️⭐️ |
|2024.06| 🔥🔥[**DiTFastAttn**] DiTFastAttn: Attention Compression for Diffusion Transformer Models(@Zhihang Yuan etc)|[[pdf]](https://arxiv.org/pdf/2406.08552) | [[DiTFastAttn]](https://github.com/thu-nics/DiTFastAttn) ![](https://img.shields.io/github/stars/thu-nics/DiTFastAttn.svg?style=social)|⭐️⭐️ |
|2024.06| 🔥🔥[**∆-DiT**] ∆-DiT: A Training-Free Acceleration Method Tailored for Diffusion Transformers(@Fudan University)|[[pdf]](https://arxiv.org/pdf/2406.01125) | ⚠️|⭐️⭐️ |
|2024.09| 🔥🔥[**TokenCache**] Token Caching for Diffusion Transformer Acceleration(@Institute of Automation, Chinese Academy of Sciences)|[[pdf]](https://arxiv.org/pdf/2409.18523) | ⚠️|⭐️⭐️ |
|2024.11| 🔥🔥[**AdaCache**] Adaptive Caching for Faster Video Generation with Diffusion Transformers(@Meta)|[[pdf]](https://adacache-dit.github.io/clarity/adacache_meta.pdf) | [[AdaCache]](https://github.com/AdaCache-DiT/AdaCache) ![](https://img.shields.io/github/stars/AdaCache-DiT/AdaCache.svg?style=social)|⭐️⭐️ |
|2024.11| 🔥🔥[**TeaCache**] Timestep Embedding Tells: It’s Time to Cache for Video Diffusion Model(@Alibaba)| [[pdf]](https://arxiv.org/pdf/2411.19108) | [[TeaCache]](https://github.com/LiewFeng/TeaCache) ![](https://img.shields.io/github/stars/LiewFeng/TeaCache.svg?style=social)|⭐️⭐️ |
Expand Down