"image generation" Papers

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.

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.

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.

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.

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.

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.

A Bias-Variance-Covariance Decomposition of Kernel Scores for Generative Models

Sebastian Gregor Gruber, Florian Buettner

Accelerating Parallel Sampling of Diffusion Models

Zhiwei Tang, Jiasheng Tang, Hao Luo et al.

ArtBank: Artistic Style Transfer with Pre-trained Diffusion Model and Implicit Style Prompt Bank

Zhanjie Zhang, Quanwei Zhang, Wei Xing et al.

ArtWhisperer: A Dataset for Characterizing Human-AI Interactions in Artistic Creations

Kailas Vodrahalli, James Zou

Characteristic Guidance: Non-linear Correction for Diffusion Model at Large Guidance Scale

Candi Zheng, Yuan LAN

Completing Visual Objects via Bridging Generation and Segmentation

Xiang Li, Yinpeng Chen, Chung-Ching Lin et al.

Critical windows: non-asymptotic theory for feature emergence in diffusion models

Marvin Li, Sitan Chen

Directly Denoising Diffusion Models

Dan Zhang, Jingjing Wang, Feng Luo

Feedback Efficient Online Fine-Tuning of Diffusion Models

Masatoshi Uehara, Yulai Zhao, Kevin Black et al.

Going beyond Compositions, DDPMs Can Produce Zero-Shot Interpolations

Justin Deschenaux, Igor Krawczuk, Grigorios Chrysos et al.

Image Content Generation with Causal Reasoning

Xiaochuan Li, Baoyu Fan, Run Zhang et al.

Kepler codebook

Junrong Lian, Ziyue Dong, Pengxu Wei et al.

LayerMerge: Neural Network Depth Compression through Layer Pruning and Merging

Jinuk Kim, Marwa El Halabi, Mingi Ji et al.

MS$^3$D: A RG Flow-Based Regularization for GAN Training with Limited Data

Jian Wang, Xin Lan, Yuxin Tian et al.

Multi-Architecture Multi-Expert Diffusion Models

Yunsung Lee, Jin-Young Kim, Hyojun Go et al.

Neural Diffusion Models

Grigory Bartosh, Dmitry Vetrov, Christian Andersson Naesseth

On Inference Stability for Diffusion Models

Viet Nguyen, Giang Vu, Tung Nguyen Thanh et al.

On the Trajectory Regularity of ODE-based Diffusion Sampling

Defang Chen, Zhenyu Zhou, Can Wang et al.

Operator-Learning-Inspired Modeling of Neural Ordinary Differential Equations

Woojin Cho, Seunghyeon Cho, Hyundong Jin et al.

Quantum Implicit Neural Representations

Jiaming Zhao, Wenbo Qiao, Peng Zhang et al.

Reducing Spatial Fitting Error in Distillation of Denoising Diffusion Models

Shengzhe Zhou, Zejian Li, Shengyuan Zhang et al.

ReGround: Improving Textual and Spatial Grounding at No Cost

Phillip (Yuseung) Lee, Minhyuk Sung

S2WAT: Image Style Transfer via Hierarchical Vision Transformer Using Strips Window Attention

Chiyu Zhang, Xiaogang Xu, Lei Wang et al.

Scalable Wasserstein Gradient Flow for Generative Modeling through Unbalanced Optimal Transport

Jaemoo Choi, Jaewoong Choi, Myungjoo Kang

The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling

Jiajun Ma, Shuchen Xue, Tianyang Hu et al.

Trainable Highly-expressive Activation Functions

Irit Chelly, Shahaf Finder, Shira Ifergane et al.

Turning Waste into Wealth: Leveraging Low-Quality Samples for Enhancing Continuous Conditional Generative Adversarial Networks