"image generation" Papers
99 papers found • Page 1 of 2
Addressing Representation Collapse in Vector Quantized Models with One Linear Layer
Yongxin Zhu, Bocheng Li, Yifei Xin et al.
Align Your Flow: Scaling Continuous-Time Flow Map Distillation
Amirmojtaba Sabour, Sanja Fidler, Karsten Kreis
Anti-Exposure Bias in Diffusion Models
Junyu Zhang, Daochang Liu, Eunbyung Park et al.
Are Images Indistinguishable to Humans Also Indistinguishable to Classifiers?
Zebin You, Xinyu Zhang, Hanzhong Guo 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
Contrastive Test-Time Composition of Multiple LoRA Models for Image Generation
Tuna Meral, Enis Simsar, Federico Tombari et al.
CREA: A Collaborative Multi-Agent Framework for Creative Image Editing and Generation
Kavana Venkatesh, Connor Dunlop, Pinar Yanardag
Decouple-Then-Merge: Finetune Diffusion Models as Multi-Task Learning
Qianli Ma, Xuefei Ning, Dongrui Liu et al.
Devil is in the Detail: Towards Injecting Fine Details of Image Prompt in Image Generation via Conflict-free Guidance and Stratified Attention
Kyungmin Jo, Jooyeol Yun, Jaegul Choo
DiC: Rethinking Conv3x3 Designs in Diffusion Models
Yuchuan Tian, Jing Han, Chengcheng Wang 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
Edit360: 2D Image Edits to 3D Assets from Any Angle
Junchao Huang, Xinting Hu, Shaoshuai Shi et al.
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.
FlexiDiT: Your Diffusion Transformer Can Easily Generate High-Quality Samples with Less Compute
Sotiris Anagnostidis, Gregor Bachmann, Yeongmin Kim et al.
FUDOKI: Discrete Flow-based Unified Understanding and Generation via Kinetic-Optimal Velocities
Jin Wang, Yao Lai, Aoxue Li et al.
Generator Matching: Generative modeling with arbitrary Markov processes
Peter Holderrieth, Marton Havasi, Jason Yim 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.
Hierarchical Koopman Diffusion: Fast Generation with Interpretable Diffusion Trajectory
Hanru Bai, Weiyang Ding, Difan Zou
IDEA-Bench: How Far are Generative Models from Professional Designing?
Chen Liang, Lianghua Huang, Jingwu Fang 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.
Janus-Pro-R1: Advancing Collaborative Visual Comprehension and Generation via Reinforcement Learning
Kaihang Pan, Yang Wu, Wendong Bu 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.
Linear Differential Vision Transformer: Learning Visual Contrasts via Pairwise Differentials
Yifan Pu, Jixuan Ying, Qixiu Li 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.
One Step Diffusion via Shortcut Models
Kevin Frans, Danijar Hafner, Sergey Levine 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.
Rethinking Diffusion Posterior Sampling: From Conditional Score Estimator to Maximizing a Posterior
Tongda Xu, Xiyan Cai, Xinjie Zhang et al.
Re-ttention: Ultra Sparse Visual Generation via Attention Statistical Reshape
Ruichen Chen, Keith Mills, Liyao Jiang et al.