Poster "image generation" Papers
57 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.
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.
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.
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.
Proper Hölder-Kullback Dirichlet Diffusion: A Framework for High Dimensional Generative Modeling
Wanpeng Zhang, Yuhao Fang, Xihang Qiu et al.
REPA-E: Unlocking VAE for End-to-End Tuning of Latent Diffusion Transformers
Xingjian Leng, Jaskirat Singh, Yunzhong Hou 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
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.
ArtWhisperer: A Dataset for Characterizing Human-AI Interactions in Artistic Creations
Kailas Vodrahalli, James Zou
Auto-GAS: Automated Proxy Discovery for Training-free Generative Architecture Search
Lujun Li, Haosen SUN, Shiwen Li et al.
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.
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.
Neural Diffusion Models
Grigory Bartosh, Dmitry Vetrov, Christian Andersson Naesseth
On the Trajectory Regularity of ODE-based Diffusion Sampling
Defang Chen, Zhenyu Zhou, Can Wang et al.
Quantum Implicit Neural Representations
Jiaming Zhao, Wenbo Qiao, Peng Zhang et al.