2025 "image generation" Papers
40 papers found
Addressing Representation Collapse in Vector Quantized Models with One Linear Layer
Yongxin Zhu, Bocheng Li, Yifei Xin et al.
Boosting Latent Diffusion with Perceptual Objectives
Tariq Berrada, Pietro Astolfi, Melissa Hall et al.
Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient
Zigeng Chen, Xinyin Ma, Gongfan Fang et al.
Color Conditional Generation with Sliced Wasserstein Guidance
Alexander Lobashev, Maria Larchenko, Dmitry Guskov
Decouple-Then-Merge: Finetune Diffusion Models as Multi-Task Learning
Qianli Ma, Xuefei Ning, Dongrui Liu et al.
Distribution Backtracking Builds A Faster Convergence Trajectory for Diffusion Distillation
Shengyuan Zhang, Ling Yang, Zejian Li et al.
Dynamic Diffusion Transformer
Wangbo Zhao, Yizeng Han, Jiasheng Tang et al.
Easing Training Process of Rectified Flow Models Via Lengthening Inter-Path Distance
Shifeng Xu, Yanzhu Liu, Adams Kong
End-to-End Multi-Modal Diffusion Mamba
Chunhao Lu, Qiang Lu, Meichen Dong et al.
Entropic Time Schedulers for Generative Diffusion Models
Dejan Stancevic, Florian Handke, Luca Ambrogioni
Faster Inference of Flow-Based Generative Models via Improved Data-Noise Coupling
Aram Davtyan, Leello Dadi, Volkan Cevher et al.
FUDOKI: Discrete Flow-based Unified Understanding and Generation via Kinetic-Optimal Velocities
Jin Wang, Yao Lai, Aoxue Li et al.
GMValuator: Similarity-based Data Valuation for Generative Models
Jiaxi Yang, Wenlong Deng, Benlin Liu et al.
Halton Scheduler for Masked Generative Image Transformer
Victor Besnier, Mickael Chen, David Hurych et al.
InCoDe: Interpretable Compressed Descriptions For Image Generation
Armand Comas, Aditya Chattopadhyay, Feliu Formosa et al.
Inference-Time Scaling for Flow Models via Stochastic Generation and Rollover Budget Forcing
Jaihoon Kim, Taehoon Yoon, Jisung Hwang et al.
Informed Correctors for Discrete Diffusion Models
Yixiu Zhao, Jiaxin Shi, Feng Chen et al.
Learning Diffusion Models with Flexible Representation Guidance
Chenyu Wang, Cai Zhou, Sharut Gupta et al.
LEDiT: Your Length-Extrapolatable Diffusion Transformer without Positional Encoding
Shen Zhang, Siyuan Liang, Yaning Tan et al.
LMFusion: Adapting Pretrained Language Models for Multimodal Generation
Weijia Shi, Xiaochuang Han, Chunting Zhou et al.
MergeVQ: A Unified Framework for Visual Generation and Representation with Disentangled Token Merging and Quantization
Siyuan Li, Luyuan Zhang, Zedong Wang et al.
MET3R: Measuring Multi-View Consistency in Generated Images
Mohammad Asim, Christopher Wewer, Thomas Wimmer et al.
MUNBa: Machine Unlearning via Nash Bargaining
Jing Wu, Mehrtash Harandi
Nested Diffusion Models Using Hierarchical Latent Priors
Xiao Zhang, Ruoxi Jiang, Rebecca Willett et al.
Not All Parameters Matter: Masking Diffusion Models for Enhancing Generation Ability
Lei Wang, Senmao Li, Fei Yang et al.
Parallel Sequence Modeling via Generalized Spatial Propagation Network
Hongjun Wang, Wonmin Byeon, Jiarui Xu et al.
PFDiff: Training-Free Acceleration of Diffusion Models Combining Past and Future Scores
Guangyi Wang, Yuren Cai, lijiang Li et al.
PID-controlled Langevin Dynamics for Faster Sampling on Generative Models
Hongyi Chen, Jianhai Shu, Jingtao Ding et al.
PlanGen: Towards Unified Layout Planning and Image Generation in Auto-Regressive Vision Language Models
Runze He, bo cheng, Yuhang Ma et al.
Proper Hölder-Kullback Dirichlet Diffusion: A Framework for High Dimensional Generative Modeling
Wanpeng Zhang, Yuhao Fang, Xihang Qiu et al.
Rectified Diffusion: Straightness Is Not Your Need in Rectified Flow
Fu-Yun Wang, Ling Yang, Zhaoyang Huang et al.
REPA-E: Unlocking VAE for End-to-End Tuning of Latent Diffusion Transformers
Xingjian Leng, Jaskirat Singh, Yunzhong Hou et al.
Representation Entanglement for Generation: Training Diffusion Transformers Is Much Easier Than You Think
Ge Wu, Shen Zhang, Ruijing Shi et al.
SCoT: Unifying Consistency Models and Rectified Flows via Straight-Consistent Trajectories
zhangkai wu, Xuhui Fan, Hongyu Wu et al.
Simple ReFlow: Improved Techniques for Fast Flow Models
Beomsu Kim, Yu-Guan Hsieh, Michal Klein et al.
TADA: Improved Diffusion Sampling with Training-free Augmented DynAmics
Tianrong Chen, Huangjie Zheng, David Berthelot et al.
Truncated Consistency Models
Sangyun Lee, Yilun Xu, Tomas Geffner et al.
USP: Unified Self-Supervised Pretraining for Image Generation and Understanding
Xiangxiang Chu, Renda Li, Yong Wang
VETA-DiT: Variance-Equalized and Temporally Adaptive Quantization for Efficient 4-bit Diffusion Transformers
Qinkai XU, yijin liu, YangChen et al.
Z-Magic: Zero-shot Multiple Attributes Guided Image Creator
Yingying Deng, Xiangyu He, Fan Tang et al.