"image generation" Papers
154 papers found • Page 2 of 4
Conference
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.
LANTERN: Accelerating Visual Autoregressive Models with Relaxed Speculative Decoding
Doohyuk Jang, Sihwan Park, June Yong Yang et al.
LaRender: Training-Free Occlusion Control in Image Generation via Latent Rendering
Xiaohang Zhan, Dingming Liu
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.
MCGAN: Enhancing GAN Training with Regression-Based Generator Loss
Baoren Xiao, Hao Ni, Weixin Yang
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
Neighboring Autoregressive Modeling for Efficient Visual Generation
Yefei He, Yuanyu He, Shaoxuan He 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.
Numerical Pruning for Efficient Autoregressive Models
Xuan Shen, Zhao Song, Yufa Zhou 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.
RBench-V: A Primary Assessment for Visual Reasoning Models with Multimodal Outputs
Meng-Hao Guo, Xuanyu Chu, Qianrui Yang et al.
Rectified Diffusion: Straightness Is Not Your Need in Rectified Flow
Fu-Yun Wang, Ling Yang, Zhaoyang Huang et al.
Rectifying Magnitude Neglect in Linear Attention
Qihang Fan, Huaibo Huang, Yuang Ai et al.
REPA-E: Unlocking VAE for End-to-End Tuning of Latent Diffusion Transformers
Xingjian Leng, Jaskirat Singh, Yunzhong Hou et al.
REPA Works Until It Doesn’t: Early-Stopped, Holistic Alignment Supercharges Diffusion Training
Ziqiao Wang, Wangbo Zhao, Yuhao Zhou 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.
SaRA: High-Efficient Diffusion Model Fine-tuning with Progressive Sparse Low-Rank Adaptation
Teng Hu, Jiangning Zhang, Ran Yi 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.
Sparse Image Synthesis via Joint Latent and RoI Flow
Ziteng Gao, Jay Zhangjie Wu, Mike Zheng Shou
StelLA: Subspace Learning in Low-rank Adaptation using Stiefel Manifold
Zhizhong Li, Sina Sajadmanesh, Jingtao Li et al.
SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding
Hao Li, Changyao TIAN, Jie Shao et al.
TADA: Improved Diffusion Sampling with Training-free Augmented DynAmics
Tianrong Chen, Huangjie Zheng, David Berthelot et al.
TCAQ-DM: Timestep-Channel Adaptive Quantization for Diffusion Models
Haocheng Huang, Jiaxin Chen, Jinyang Guo et al.
The Superposition of Diffusion Models Using the Itô Density Estimator
Marta Skreta, Lazar Atanackovic, Joey Bose et al.
ToddlerDiffusion: Interactive Structured Image Generation with Cascaded Schrödinger Bridge
Eslam Abdelrahman, Liangbing Zhao, Tao Hu et al.
TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation
Liao Qu, Huichao Zhang, Yiheng Liu et al.
Towards Stabilized and Efficient Diffusion Transformers through Long-Skip-Connections with Spectral Constraints
Guanjie Chen, Xinyu Zhao, Yucheng Zhou et al.
TREAD: Token Routing for Efficient Architecture-agnostic Diffusion Training
Felix Krause, Timy Phan, Ming Gui et al.
Truncated Consistency Models
Sangyun Lee, Yilun Xu, Tomas Geffner et al.
Universal Few-shot Spatial Control for Diffusion Models
Kiet Nguyen, Chanhyuk Lee, Donggyun Kim et al.
Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin
Fangyikang Wang, Hubery Yin, Lei Qian 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.
VQ4DiT: Efficient Post-Training Vector Quantization for Diffusion Transformers
Juncan Deng, Shuaiting Li, Zeyu Wang et al.
Warm Diffusion: Recipe for Blur-Noise Mixture Diffusion Models
Hao-Chien Hsueh, Wen-Hsiao Peng, Ching-Chun Huang