"image generation" Papers
154 papers found • Page 1 of 4
Conference
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
An Image-like Diffusion Method for Human-Object Interaction Detection
Xiaofei Hui, Haoxuan Qu, Hossein Rahmani et al.
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.
CatVTON: Concatenation Is All You Need for Virtual Try-On with Diffusion Models
Zheng Chong, Xiao Dong, Haoxiang Li et al.
CHORDS: Diffusion Sampling Accelerator with Multi-core Hierarchical ODE Solvers
Jiaqi Han, Haotian Ye, Puheng Li et al.
CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up
Songhua Liu, Zhenxiong Tan, Xinchao Wang
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
Composition and Alignment of Diffusion Models using Constrained Learning
Shervin Khalafi, Ignacio Hounie, Dongsheng Ding et al.
Contrastive Test-Time Composition of Multiple LoRA Models for Image Generation
Tuna Meral, Enis Simsar, Federico Tombari et al.
CPSample: Classifier Protected Sampling for Guarding Training Data During Diffusion
Joshua Kazdan, Hao Sun, Jiaqi Han 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.
Denoising with a Joint-Embedding Predictive Architecture
Chen Dengsheng, Jie Hu, Xiaoming Wei 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
DiCo: Revitalizing ConvNets for Scalable and Efficient Diffusion Modeling
Yuang Ai, Qihang Fan, Xuefeng Hu et al.
DiC: Rethinking Conv3x3 Designs in Diffusion Models
Yuchuan Tian, Jing Han, Chengcheng Wang et al.
Diffusion Model Patching via Mixture-of-Prompts
Seokil Ham, Sangmin Woo, Jin-Young Kim et al.
Distribution Backtracking Builds A Faster Convergence Trajectory for Diffusion Distillation
Shengyuan Zhang, Ling Yang, Zejian Li et al.
Do WGANs succeed because they minimize the Wasserstein Distance? Lessons from Discrete Generators
Ariel Elnekave, Yair Weiss
DreamOmni: Unified Image Generation and Editing
Bin Xia, Yuechen Zhang, Jingyao 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
EVODiff: Entropy-aware Variance Optimized Diffusion Inference
Shigui Li, Wei Chen, Delu Zeng
Fast Direct: Query-Efficient Online Black-box Guidance for Diffusion-model Target Generation
Kim Yong Tan, YUEMING LYU, Ivor Tsang et al.
Faster Inference of Flow-Based Generative Models via Improved Data-Noise Coupling
Aram Davtyan, Leello Dadi, Volkan Cevher et al.
Finding Local Diffusion Schrödinger Bridge using Kolmogorov-Arnold Network
Xingyu Qiu, Mengying Yang, Xinghua Ma et al.
FlexiDiT: Your Diffusion Transformer Can Easily Generate High-Quality Samples with Less Compute
Sotiris Anagnostidis, Gregor Bachmann, Yeongmin Kim et al.
Flow Matching with General Discrete Paths: A Kinetic-Optimal Perspective
Neta Shaul, Itai Gat, Marton Havasi 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.
GeoDiffusion: A Training-Free Framework for Accurate 3D Geometric Conditioning in Image Generation
Phillip Mueller, Talip Ünlü, Sebastian Schmidt et al.
Glauber Generative Model: Discrete Diffusion Models via Binary Classification
Harshit Varma, Dheeraj Nagaraj, Karthikeyan Shanmugam
GMValuator: Similarity-based Data Valuation for Generative Models
Jiaxi Yang, Wenlong Deng, Benlin Liu et al.
GPSToken: Gaussian Parameterized Spatially-adaptive Tokenization for Image Representation and Generation
Zhengqiang ZHANG, Rongyuan Wu, Lingchen Sun et al.
Halton Scheduler for Masked Generative Image Transformer
Victor Besnier, Mickael Chen, David Hurych et al.
Harmonizing Visual Representations for Unified Multimodal Understanding and Generation
Size Wu, Wenwei Zhang, Lumin Xu 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.
Image-level Memorization Detection via Inversion-based Inference Perturbation
Yue Jiang, Haokun Lin, Yang Bai et al.
Improved Noise Schedule for Diffusion Training
Tiankai Hang, Shuyang Gu, Jianmin Bao et al.
Improved Sampling Algorithms for Lévy-Itô Diffusion Models
Vadim Popov, Assel Yermekova, Tasnima Sadekova 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.