Text-To-Image

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Text-To-Image

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Image Generation

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Large-Scale Image Generation

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Text-To-Image Diffusion Models

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Visual Generation

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Orthogonal Negative Guidance in Attention Feature Space for Text-to-Image Generation
May 28, 2026Jungmin Ko, Jungwon Park, Jimyeong Kim +3Text-To-Image
Rethinking FID Through the Geometry of the Reference Dataset
May 28, 2026Yunghee Lee, Byeonghyun PakFréchet Inception Distance Evaluation Metrics
Compositional Text-to-Image Generation Via Region-aware Bimodal Direct Preference Optimization
May 27, 2026Zhuohan Liu, Wujian Peng, Yitong Chen +1Text-To-Image Text Generation
DebFilter: Eradicating Biases Stashed in Value
May 27, 2026Seung Hyuk Lee, Songkuk KimText-To-Image Diffusion Models Implicit Bias
No Safe Dose: How Training Data Drives Unsafe Image Generation
May 27, 2026Felix Friedrich, Lukas Helff, Niharika Hegde +2Text-To-Image Large Language Model Safety
Qwen-Image-Bench: From Generation to Creation in Text-to-Image Evaluation
May 27, 2026Niantong Li, Guangzheng Hu, Weixu Qiao +35Text-To-Image Creativity
Stay Fair! Ensuring Group Fairness in Diffusion Models Across Guidance Scales
May 27, 2026Myeongsoo Kim, Eunji Kim, Minwoo Chae +1Fairness Interventions Implicit Bias
Towards Controllable Image Generation through Representation-Conditioned Diffusion Models
May 26, 2026Nithesh Chandher Karthikeyan, Jonas Unger, Gabriel EilertsenText-To-Image Diffusion Models Self-Supervised
MRT: Masked Region Transformer for Layered Image Generation and Editing at Scale
May 26, 2026Zhicong Tang, Zhao Zhang, Jingye Chen +6Large-Scale Image Generation
Diffusion-Based Ukrainian Handwritten Text Generation with Cross-Domain Style Transfer
May 26, 2026Andrii Ahitoliev, Pavlo BerezinPhotorealistic Style Transfer Text-To-Image Diffusion Models
Do Modern Post-Hoc Watermarking Methods Beat Broken-Arrows?
May 26, 2026Enoal Gesny, Eva GiboulotWatermarking Watermarks
Leveraging Text-to-Image Diffusion Models for Unsupervised Visual Object Tracking
May 26, 2026Zhengbo Zhang, Zhigang Tu, Junsong Yuan +2Multi-Object Tracking Photometric Supervision
RT-Lynx: Putting the GEMM Sparsity In a Right Way for Diffusion Models
May 26, 2026Xing Cong, Hanlin Tang, Kan Liu +3Multimodal Diffusion Transformers Sparse Expert Activation
Beyond Pairwise Preferences: Listwise Reward-Aware Alignment for Diffusion Models
May 26, 2026Austin Wang, Jiaqi Han, Stefano Ermon +1Text-To-Image Diffusion Models Training-Free Reward Alignment
Erased but Exploitable: Black-box Embedding-Aware Prompting Against Unlearned Text-to-Image Diffusion Models
May 25, 2026Arian Komaei Koma, Seyed Amir Kasaei, AmirMahdi Sadeghzadeh +1Text-To-Image Diffusion Models Adversarial Prompting
Squeezing Capacity from Multimodal Large Language Models for Subject-driven Generation
May 25, 2026Shuhong Zheng, Aashish Kumar Misraa, Yu-Teng Li +2Large-Scale Image Generation Multimodal Generation
Reinforcing Few-step Generators via Reward-Tilted Distribution Matching
May 25, 2026Yushi Huang, Xiangxin Zhou, Ruoyu Wang +3Text-To-Image Generative Models
Everything at Every Scale: Scale-Invariant Diffusion with Continuous Super-Resolution
May 25, 2026Zixin Jessie Chen, Zhuo Chen, Archer Wang +4Super-Resolution Framework Large-Scale Image Generation
DyCoRM: Dynamic Criterion-Aware Reward Modeling for Text-to-Image Generation
May 25, 2026Jiaying Qian, Ziheng Jia, Qian Zhang +5Text-To-Image Reasoning-Aware Reward
Concept Unlearning via Cross-Attention Activation Projection for Diffusion Models
May 25, 2026Saemi Moon, Suhyeon Jun, Seoyeon Lee +1Text-To-Image Diffusion Models Unlearning Aims
AI-T2I: Aggregating-and-Isolating Cross-Attention to Diffusion Models for Text-to-Image Synthesis
May 25, 2026Shipeng Cao, Biao Qian, Haipeng Liu +2Text-To-Image Diffusion Models Text-To-Image
Towards Anatomically Plausible Human Image Generation via Synthetic Localized Preferences
May 25, 2026Bao Li, Yuliang Xiu, Zhen LiuAnatomical Priors Video-Text Alignment
Diffusion Image Generation with Explicit Modeling of Data Manifold Geometry
May 25, 2026Duoduo Xue, Zhiyu Zhu, Junhui HouImage Generation Generative Models
Mosaic: Compositional Multi-Concept Erasure via Vector Field Blending
May 25, 2026Junseok Ko, Jungwoo Kim, Jong-Seok LeeConcept Erasure Text-To-Image
MAIL++: Multi-Modal Bi-directional Agent Layer for Vision-Language Models
May 25, 2026Kaixiang Chen, Pengfei Fang, Hui XueCross-Modal Learning Multimodal Agents
ERNIE-Image Technical Report
May 25, 2026Jiaxiang Liu, Zhida Feng, Pengyu Zou +46Text-To-Image Multimodal Diffusion Transformers
Geometry-Aware Image Flow Matching
May 24, 2026Junho Lee, Kwanseok Kim, Joonseok LeeHierarchical Flow Matching Statistical Manifold
Injecting Image Guidance into Text-Conditioned Diffusion Models at Inference
May 24, 2026Agata Żywot, Iason Skylitsis, Thijmen Nijdam +4Text-To-Image Diffusion Models Self-Supervised Reconstruction Method
BFS: Back-to-Front Layered Image Synthesis via Knowledge Transfer
May 24, 2026Kyoungkook Kang, Gyujin Sim, Sunghyun ChoLarge-Scale Image Generation Generative Models
HoloFair: Unified T2I Fairness Evaluation and Fair-GRPO Debiasing
May 23, 2026Ruyi Chen, Lu Zhou, Xiaogang Xu +3Text-To-Image Flow-Grpo
VectorArk: Learning Practical Image Vectorization with Rounded Polygon Representation
May 23, 2026Tarun Gehlaut, Difan Liu, Charu Bansal +5Scalable Vector Graphic Large Vision Language Models
Diffusion Domain Expansion: Learning to Coordinate Pre-trained Diffusion Models
May 22, 2026Egor Lifar, Semyon Savkin, Timur Garipov +2Image Generation Neural Network
Coloring the Noise: Adversarial Sobolev Alignment for Faithful Image Super Resolution
May 22, 2026Hongbo Wang, Huaibo Huang, Pin Wang +3Generative Super-Resolution Large-Scale Image Generation
Composing People Together: Iterative Pose-Image Generation for Multi-Person Interaction Scenes
May 22, 2026Wenxuan Peng, Bharath Hariharan, Hadar Averbuch-ElorLarge-Scale Image Generation Indoor Scene Generation
SeqLoRA: Bilevel Orthogonal Adaptation for Continual Multi-Concept Generation
May 21, 2026Javad Parsa, Enis Simsar, Amir Joudaki +2Text-To-Image Diffusion Models Continual Learning Methods
Live Music Diffusion Models: Efficient Fine-Tuning and Post-Training of Interactive Diffusion Music Generators
May 21, 2026Zachary Novack, Stephen Brade, Haven Kim +8Music Generation Conversational Music Recommendation
SEGA: Spectral-Energy Guided Attention for Resolution Extrapolation in Diffusion Transformers
May 21, 2026Javad Rajabi, Kimia Shaban, Koorosh Roohi +2Multimodal Diffusion Transformers Text-To-Image
AtelierEval: Agentic Evaluation of Humans & LLMs as Text-to-Image Prompters
May 21, 2026Hanjun Luo, Zhimu Huang, Sylvia Chung +6Text-To-Image Agentic Evaluations
MaSC: A Masked Similarity Metric for Evaluating Concept-Driven Generation
May 21, 2026Patryk Bartkowiak, Lennart Petersen, Bartosz Kotrys +3Text-To-Image Semantic Similarity Metrics
S2ED: From Story to Executable Descriptions for Consistency-Aware Story Illustration
May 21, 2026Sijing Yin, Jiamou Liu, Xiao Tang +2Llm-Generated Stories Narratives
Flow-based Gaussian Splatting for Continuous-Scale Remote Sensing Image Super-Resolution
May 21, 2026Jiangwei Mo, Xi Lu, Hanlin WuGenerative Super-Resolution Large-Scale Image Generation
Safeguarding Text-to-Image Generative Models Against Unauthorized Knowledge Distillation
May 21, 2026Yilan Gao, Sida Huang, Hongyuan Zhang +1Adversarial Examples Text-To-Image
UniVL: Unified Vision-Language Embedding for Spatially Grounded Contextual Image Generation
May 20, 2026Jiayun Wang, Yu Wang, Weijie Gan +2Image Generation Vision-Language
GenEvolve: Self-Evolving Image Generation Agents via Tool-Orchestrated Visual Experience Distillation
May 20, 2026Sixiang Chen, Zhaohu Xing, Tian Ye +7Image Generation Self-Evolution
Lens: Rethinking Training Efficiency for Foundational Text-to-Image Models
May 20, 2026Dong Chen, Fangyun Wei, Ziyu Wan +18Text-To-Image Image-Text Pairs
OcclusionFormer: Arranging Z-Order for Layout-Grounded Image Generation
May 20, 2026Ziye Li, Henghui DingDiverse Occlusion-And-Revelation Scenarios Occlusion
MONET: A Massive, Open, Non-redundant and Enriched Text-to-image dataset
May 20, 2026Benjamin Aubin, Gonzalo Iñaki Quintana, Onur Tasar +4Text-To-Image Massive
RankE: End-to-End Post-Training for Discrete Text-to-Image Generation with Decoder Co-Evolution
May 20, 2026Siyong Jian, Siyuan Li, Luyuan Zhang +5Text-To-Image Large Language Model Quantization
Linear-DPO: Linear Direct Preference Optimization for Diffusion and Flow-Matching Generative Models
May 20, 2026Kesong Li, Yixuan Xu, Kuo-kun Tseng +3Text-To-Image Diffusion Models Text-To-Image
TextSculptor: Training and Benchmarking Scene Text Editing
May 20, 2026Yiheng Lin, Siyu Jiao, Xiaohan Lan +12Text-To-Image Multimodal Benchmarks
Decomposing Subject-Driven Image Generation via Intermediate Structural Prediction
May 20, 2026Hanzhong Guo, Yizhou YuText-To-Image Few-Step Generation
AttriStory: Fine-grained Attribute Realization for Visual Storytelling with Diffusion Models
May 20, 2026Manogna Sreenivas, Rohit Kumar, Soma BiswasVisual Storytelling Llm-Generated Stories
TASTE: A Designer-Annotated Multi-Dimensional Preference Dataset for AI-Generated Graphic Design
May 20, 2026Haonan Zhu, Elad Hirsch, Alexandria Minetti +3Text-To-Image Aesthetics
Pareto-Enhanced Portrait Generation: Vision-Aligned Text Supervision for Alignment, Realism, and Aesthetics
May 20, 2026Yunlong Wang, Jinjin Shi, Wenbin Gao +3Text-To-Image Diffusion Models Video-Text Alignment
Head-Aware Key-Value Compression for Efficient Autoregressive Image Generation
May 20, 2026Guotao Liang, Baoquan Zhang, Zhiyuan Wen +1Autoregressive Image Generation Key-Value Cache Compression
FullFlow: Upgrading Text-to-Image Flow Matching Models for Bidirectional Vision--Language Generation
May 19, 2026Eric Tillmann Bill, Enis Simsar, Alessio Tonioni +1Text-To-Image Diffusion Models Large Vision Language Models
PixVerve: Advancing Native UHR Image Generation to 100MP with a Large-Scale High-Quality Dataset
May 19, 2026Haojun Chen, Haoyang He, Chengming Xu +11High-Resolution Vision Datasets
MetaEarth-MM: Unified Multimodal Remote Sensing Image Generation with Scene-centered Joint Modeling
May 19, 2026Zhiping Yu, Chenyang Liu, Jinqi Cao +4Remote Sensing Cloud-Aware Earth Observation Sequences
Tiny-Engram: Trigger-Indexed Concept Tables for Generative Vision
May 19, 2026Runyuan Cai, Yiming Wang, Yu Lin +1Visual Generation Visual Memory
A Framework for Evaluating Zero-Shot Image Generation in Concept-based Explainability
May 19, 2026Giacomo Astolfi, Matteo Bianchi, Riccardo Campi +2Text-To-Image Explainable Artificial Intelligence

May 28, 2026 · cs.CVJ/K move · Enter open · S save

Orthogonal Negative Guidance in Attention Feature Space for Text-to-Image Generation

Jungmin Ko, Jungwon Park, Jimyeong Kim, Changin Choi+2

Interdisciplinary Program in Artificial Intelligence, Seoul National University · Research Institute for Convergence Science, Seoul National University · Daegu Gyeongbuk Institute of Science and Technology · Artificial Intelligence Institute, Seoul National University · Samsung Advanced Institute of Technology, Samsung Electronics Co., Ltd

Text-to-image (T2I) models have become increasingly capable of generating high-quality images. Yet, enforcing the explicit absence of a specified object or attribute remains a fundamentally challenging problem. Existing approaches, including prompt negation, post-hoc editing, and negative guidance, remain insufficient for explicit concept suppression, often failing to remove the target concept or degrading overall image quality. To this end, we propose Orthogonal Negative Guidance in attention feature space, a training-free method that operates in the attention output space of MM-DiT-based T2I transformers. Our method orthogonalizes negative-prompt attention features with respect to positive-prompt features and subtracts only the orthogonal component, suppressing unwanted concepts while preserving desired semantics. Experiments on FLUX-dev and FLUX-schnell show that our method achieves favorable trade-offs between concept suppression, prompt alignment, and image quality. In human evaluation, our method outperforms the second-best baseline by 18.78%. We further show that our method supports multi-concept suppression and adjustable concept suppression.

Text-To-Image

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