Cover Image

TCAQ-DM: Timestep-Channel Adaptive Quantization for Diffusion Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Huang, Haocheng, Chen, Jiaxin, Guo, Jinyang, Zhan, Ruiyi, Wang, Yunhong
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

APHQ-ViT: Post-Training Quantization with Average Perturbation Hessian Based Reconstruction for Vision Transformers
by: Wu, Zhuguanyu, et al.
Published: (2025)

AdaLog: Post-Training Quantization for Vision Transformers with Adaptive Logarithm Quantizer
by: Wu, Zhuguanyu, et al.
Published: (2024)

TMPQ-DM: Joint Timestep Reduction and Quantization Precision Selection for Efficient Diffusion Models
by: Sun, Haojun, et al.
Published: (2024)

BiDM: Pushing the Limit of Quantization for Diffusion Models
by: Zheng, Xingyu, et al.
Published: (2024)

Timestep-Aware Correction for Quantized Diffusion Models
by: Yao, Yuzhe, et al.
Published: (2024)

Post-Training Quantization for Diffusion Transformer via Hierarchical Timestep Grouping
by: Ding, Ning, et al.
Published: (2025)

BinaryDM: Accurate Weight Binarization for Efficient Diffusion Models
by: Zheng, Xingyu, et al.
Published: (2024)

CTCal: Rethinking Text-to-Image Diffusion Models via Cross-Timestep Self-Calibration
by: Guo, Xiefan, et al.
Published: (2026)

MPQ-DM: Mixed Precision Quantization for Extremely Low Bit Diffusion Models
by: Feng, Weilun, et al.
Published: (2024)

Collaborative Multi-Mode Pruning for Vision-Language Models
by: Wu, Zimeng, et al.
Published: (2026)

QArtSR: Quantization via Reverse-Module and Timestep-Retraining in One-Step Diffusion based Image Super-Resolution
by: Zhu, Libo, et al.
Published: (2025)

Adaptive Non-uniform Timestep Sampling for Accelerating Diffusion Model Training
by: Kim, Myunsoo, et al.
Published: (2024)

TASR: Timestep-Aware Diffusion Model for Image Super-Resolution
by: Lin, Qinwei, et al.
Published: (2024)

TFMQ-DM: Temporal Feature Maintenance Quantization for Diffusion Models
by: Huang, Yushi, et al.
Published: (2023)

Timestep Embedding Tells: It's Time to Cache for Video Diffusion Model
by: Liu, Feng, et al.
Published: (2024)

ERTACache: Error Rectification and Timesteps Adjustment for Efficient Diffusion
by: Peng, Xurui, et al.
Published: (2025)

Tuning Timestep-Distilled Diffusion Model Using Pairwise Sample Optimization
by: Miao, Zichen, et al.
Published: (2024)

TimeStep Master: Asymmetrical Mixture of Timestep LoRA Experts for Versatile and Efficient Diffusion Models in Vision
by: Zhuang, Shaobin, et al.
Published: (2025)

Timestep-Aware Diffusion Model for Extreme Image Rescaling
by: Wang, Ce, et al.
Published: (2024)

Towards More Accurate Diffusion Model Acceleration with A Timestep Tuner
by: Xia, Mengfei, et al.
Published: (2023)

Timestep-Aware Block Masking for Efficient Diffusion Model Inference
by: He, Haodong, et al.
Published: (2026)

Learning Quantized Adaptive Conditions for Diffusion Models
by: Liang, Yuchen, et al.
Published: (2024)

Generative Multimodal Pretraining with Discrete Diffusion Timestep Tokens
by: Pan, Kaihang, et al.
Published: (2025)

HQ-DM: Single Hadamard Transformation-Based Quantization-Aware Training for Low-Bit Diffusion Models
by: Mao, Shizhuo, et al.
Published: (2025)

DDAE++: Enhancing Diffusion Models Towards Unified Generative and Discriminative Learning
by: Xiang, Weilai, et al.
Published: (2025)

EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion Models
by: He, Yefei, et al.
Published: (2023)

DyDiT++: Diffusion Transformers with Timestep and Spatial Dynamics for Efficient Visual Generation
by: Zhao, Wangbo, et al.
Published: (2025)

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation
by: Wu, Zhuguanyu, et al.
Published: (2025)

LaTtE-Flow: Layerwise Timestep-Expert Flow-based Transformer
by: Shen, Ying, et al.
Published: (2025)

Beyond Open Vocabulary: Multimodal Prompting for Object Detection in Remote Sensing Images
by: Yang, Shuai, et al.
Published: (2026)

Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning
by: Zhong, Hanwen, et al.
Published: (2025)

WaveDM: Wavelet-Based Diffusion Models for Image Restoration
by: Huang, Yi, et al.
Published: (2023)

EDA-DM: Enhanced Distribution Alignment for Post-Training Quantization of Diffusion Models
by: Liu, Xuewen, et al.
Published: (2024)

QVD: Post-training Quantization for Video Diffusion Models
by: Tian, Shilong, et al.
Published: (2024)

Exploring Multi-Timestep Multi-Stage Diffusion Features for Hyperspectral Image Classification
by: Zhou, Jingyi, et al.
Published: (2023)

ITA-MDT: Image-Timestep-Adaptive Masked Diffusion Transformer Framework for Image-Based Virtual Try-On
by: Hong, Ji Woo, et al.
Published: (2025)

Reasoning Physical Video Generation with Diffusion Timestep Tokens via Reinforcement Learning
by: Lin, Wang, et al.
Published: (2025)

AsyncDiff: Asynchronous Timestep Conditioning for Enhanced Text-to-Image Diffusion Inference
by: Xu, Longhuan, et al.
Published: (2025)

Collaborative Few-Step Distillation and Low-Bit Quantization for Wan2.2 Dual-Expert Video Diffusion Models
by: Du, Jinyang, et al.
Published: (2026)

4Diffusion: Multi-view Video Diffusion Model for 4D Generation
by: Zhang, Haiyu, et al.
Published: (2024)