"denoising process" Papers
19 papers found
Accelerating Diffusion Sampling via Exploiting Local Transition Coherence
shangwen zhu, Han Zhang, Zhantao Yang et al.
BADiff: Bandwidth Adaptive Diffusion Model
Xi Zhang, Hanwei Zhu, Yan Zhong et al.
Diffusion Models are Evolutionary Algorithms
Yanbo Zhang, Benedikt Hartl, Hananel Hazan et al.
dKV-Cache: The Cache for Diffusion Language Models
Xinyin Ma, Runpeng Yu, Gongfan Fang et al.
DynaGuide: Steering Diffusion Polices with Active Dynamic Guidance
Maximilian Du, Shuran Song
FlexiDiT: Your Diffusion Transformer Can Easily Generate High-Quality Samples with Less Compute
Sotiris Anagnostidis, Gregor Bachmann, Yeongmin Kim et al.
FreeMorph: Tuning-Free Generalized Image Morphing with Diffusion Model
Yukang Cao, Chenyang Si, Jinghao Wang et al.
Is Your Diffusion Model Actually Denoising?
Daniel Pfrommer, Zehao Dou, Christopher Scarvelis et al.
Make It Count: Text-to-Image Generation with an Accurate Number of Objects
Lital Binyamin, Yoad Tewel, Hilit Segev et al.
MRO: Enhancing Reasoning in Diffusion Language Models via Multi-Reward Optimization
Chenglong Wang, Yang Gan, Hang Zhou et al.
Not All Parameters Matter: Masking Diffusion Models for Enhancing Generation Ability
Lei Wang, Senmao Li, Fei Yang et al.
Omegance: A Single Parameter for Various Granularities in Diffusion-Based Synthesis
Xinyu Hou, Zongsheng Yue, Xiaoming Li et al.
OmniCache: A Trajectory-Oriented Global Perspective on Training-Free Cache Reuse for Diffusion Transformer Models
Huanpeng Chu, Wei Wu, Guanyu Feng et al.
On Efficiency-Effectiveness Trade-off of Diffusion-based Recommenders
Wenyu Mao, Jiancan Wu, Guoqing Hu et al.
Pioneering 4-Bit FP Quantization for Diffusion Models: Mixup-Sign Quantization and Timestep-Aware Fine-Tuning
Maosen Zhao, Pengtao Chen, Chong Yu et al.
VideoGuide: Improving Video Diffusion Models without Training Through a Teacher's Guide
Dohun Lee, Bryan Sangwoo Kim, Geon Yeong Park et al.
DECap: Towards Generalized Explicit Caption Editing via Diffusion Mechanism
Zhen Wang, Xinyun Jiang, Jun Xiao et al.
FRAG: Frequency Adapting Group for Diffusion Video Editing
Sunjae Yoon, Gwanhyeong Koo, Geonwoo Kim et al.
Noise Calibration: Plug-and-play Content-Preserving Video Enhancement using Pre-trained Video Diffusion Models
Qinyu Yang, Haoxin Chen, Yong Zhang et al.