ChangyuanWang17 / APQ-DMLinks
This is the official pytorch implementation for the paper: Towards Accurate Post-training Quantization for Diffusion Models.(CVPR24 Poster Highlight)
☆38Updated last year
Alternatives and similar repositories for APQ-DM
Users that are interested in APQ-DM are comparing it to the libraries listed below
Sorting:
- [CVPR 2024 Highlight & TPAMI 2025] This is the official PyTorch implementation of "TFMQ-DM: Temporal Feature Maintenance Quantization for…☆106Updated last month
- (ICLR 2025) BinaryDM: Accurate Weight Binarization for Efficient Diffusion Models☆25Updated last year
- ☆15Updated 7 months ago
- Implementation of Post-training Quantization on Diffusion Models (CVPR 2023)☆139Updated 2 years ago
- [ICCV2025]Generate one 2K image on single 3090 GPU!☆78Updated 2 months ago
- [NeurIPS'24]Efficient and accurate memory saving method towards W4A4 large multi-modal models.☆89Updated 10 months ago
- [CVPR 2025] Q-DiT: Accurate Post-Training Quantization for Diffusion Transformers☆70Updated last year
- [CVPR'23] SparseViT: Revisiting Activation Sparsity for Efficient High-Resolution Vision Transformer☆75Updated last year
- [ICCV 2025] QuEST: Efficient Finetuning for Low-bit Diffusion Models☆54Updated 4 months ago
- [NeurIPS 2023] Structural Pruning for Diffusion Models☆203Updated last year
- [ICLR 2024 Spotlight] This is the official PyTorch implementation of "EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Di…☆66Updated last year
- Curated list of methods that focuses on improving the efficiency of diffusion models☆44Updated last year
- The code repository of "MBQ: Modality-Balanced Quantization for Large Vision-Language Models"☆66Updated 7 months ago
- [ICCV 2025] QuantCache：Adaptive Importance-Guided Quantization with Hierarchical Latent and Layer Caching for Video Generation☆14Updated last month
- A list of papers, docs, codes about diffusion distillation.This repo collects various distillation methods for the Diffusion model. Welc…☆39Updated last year
- [ICLR'25] ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation☆130Updated 7 months ago
- Denoising Diffusion Step-aware Models (ICLR2024)☆62Updated last year
- [ICML 2025] This is the official PyTorch implementation of "ZipAR: Accelerating Auto-regressive Image Generation through Spatial Locality…☆53Updated 7 months ago
- [ICCV2025 highlight]Rectifying Magnitude Neglect in Linear Attention☆46Updated 3 months ago
- [NeurIPS 2024] Learning-to-Cache: Accelerating Diffusion Transformer via Layer Caching☆116Updated last year
- [CVPR 2025 Highlight] TinyFusion: Diffusion Transformers Learned Shallow☆144Updated 7 months ago
- PyTorch implementation of PTQ4DiT https://arxiv.org/abs/2405.16005☆38Updated last year
- [CVPR 2025] CoDe: Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient☆107Updated last month
- [ECCV 2024] Isomorphic Pruning for Vision Models☆79Updated last year
- [CVPR 2025] DiG: Scalable and Efficient Diffusion Models with Gated Linear Attention☆173Updated 8 months ago
- [CVPR 2025] The official implementation of "CacheQuant: Comprehensively Accelerated Diffusion Models"☆28Updated last week
- [ICCV 23]An approach to enhance the efficiency of Vision Transformer (ViT) by concurrently employing token pruning and token merging tech…☆101Updated 2 years ago
- The official implementation of "Sparse-vDiT: Unleashing the Power of Sparse Attention to Accelerate Video Diffusion Transformers" (arXiv …☆48Updated 5 months ago
- [NeurIPS'25] HoliTom: Holistic Token Merging for Fast Video Large Language Models☆55Updated last month
- FORA introduces simple yet effective caching mechanism in Diffusion Transformer Architecture for faster inference sampling.☆50Updated last year