Image Generation Evaluation

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12 papers in the last four weeks, up 140% on the four weeks before. 0.1% of all new papers.

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Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment
Jul 6, 2026Jiquan YuanImage Quality Assessment Image Generation Evaluation
School of Software and Microelectronics, Peking University, Beijing, China
Search Beyond What Can Be Taught: Evolving the Knowledge Boundary in Agentic Visual Generation
Jul 6, 2026Haozhe Wang, Weijia Feng, Jinpeng Yu +8Image Generation Agentic Image Generation
1Hong Kong University of Science and Technology · 3Qwen Applications · 4Imperial College London +1
PosterHarness: Turning Scientific Poster Generation into an Auditable Instruction-Following Benchmark
Jul 3, 2026Tianyi Yang, Dawei Fu, Youpeng Wu +5AI-Assisted Scientific Research Image Generation
School of Physics, Peking University
Representation Distribution Matching for One-Step Visual Generation
Jul 2, 2026Lan Feng, Wuyang Li, Eloi Zablocki +2Maximum Mean Discrepancy One-Step Generative Modeling
1EPFL, Switzerland · 2Valeo.ai, France · 3Sorbonne Universit´e, France
MIBE: Multi-subject Interaction Benchmark and Evaluator for Personalized Image Generation
Jul 1, 2026Zhihan Chen, Yuhuan Zhao, Yijie Zhu +7Subject-Driven Image Generation Identity-Preserving Image Generation
University of California, Los Angeles · University of Southern California · DeerLab LLC +5
Ask, Solve, Generate: Self-Evolving Unified Multimodal Understanding and Generation via Self-Consistency Rewards
Jun 25, 2026Ritesh Thawkar, Shravan Venkatraman, Omkar Thawakar +5Unified Multimodal Models Multimodal Generation
1Mohamed bin Zayed University of Artificial Intelligence · 4Linköping University · 3Australian National University +1
Scaling Multi-Reference Image Generation with Dynamic Reward Optimization
Jun 25, 2026Wenwang Huang, Yusen Fu, Junjie Wang +6Image Generation RL for Generative Models
Harbin Institute of Technology, Shenzhen · Independent Researcher · Shenzhen Loop Area Institute
DiffusionBench: On Holistic Evaluation of Diffusion Transformers
Jun 23, 2026Xingjian Leng, Jaskirat Singh, Zhanhao Liang +5Diffusion Transformer Image Generation Evaluation
Australian National University · Canva Research
The FID Lottery: Quantifying Hidden Randomness in Generative-Model Evaluation
Jun 18, 2026Nicolas Dufour, Alexei A. Efros, Patrick PérezML Reproducibility Image Generation Evaluation
Kyutai · UC Berkeley
BAFIS: Dataset + Framework to assess occupational Bias and Human Preference in modern Text-to-image Models
Jun 18, 2026Thomas Klassert, Adrian Ulges, Biying FuImage Generation Evaluation Demographic Bias in T2I Models
RheinMain University of Applied Sciences, Wiesbaden, Germany
Decoupling Semantics from Distortions: Multi-Scale Two-Stream Vision-Language Alignment for AI-Generated Image Quality Assessment
Jun 15, 2026Zijie MengVLM Evaluation Image Quality Assessment
Peking University
CogCanvas: A Benchmark for Evaluating Multi-Subject Reference-Based Image Generation
Jun 14, 2026Long-Bao Nguyen, Quang-Khai Le, Tam V. Nguyen +2Compositional Image Generation Identity-Preserving Image Generation
University of Science, Ho Chi Minh City, Vietnam · Vietnam National University, Ho Chi Minh City, Vietnam · University of Dayton, Ohio, United States
Vision-Encoder Behavioral Fingerprints of Image-to-Image Generative Models: A Training-Paradigm-Driven Taxonomy of Six Commercial APIs
Jun 10, 2026Hunter HillImage-to-Image Translation Image Generation Evaluation
The 1st PortraitCraft Challenge: A CVPR 2026 Workshop Competition on Portrait Composition Understanding and Generation
Jun 9, 2026Zijie Lou, Youyun Tang, Xiaochao Qu +40Compositional Image Generation Image Generation Evaluation
Can Image Models Imagine Time? ImageTime: A Novel Benchmark for Probing Visual World Modeling Through Spatiotemporal Consistency
Jun 9, 2026Xinrui Wu, Lichen HuangWorld Model Learning Conditional Image Generation
University of Electronic Science and Technology of China
Diffusing in the Right Space: A Systematic Study of Latent Diffusability
Jun 2, 2026Tianxiong Zhong, Xingye Tian, Xuebo Wang +2Latent Diffusion Models Image Tokenization
Kling Team, Kuaishou Technology
Inverting the Generation Process of Denoising Diffusion Implicit Models: Empirical Evaluation and a Novel Method
Jun 2, 2026Yan Zeng, Masanori Suganuma, Takayuki OkataniDiffusion Model Inversion Diffusion Sampling
Graduate School of Information Sciences, Tohoku University · RIKEN Center for AIP
No Free Lunch for Synthetic Images under Data Scarcity Conditions
Jun 1, 2026Borja Arroyo Galende, Alejandro Almodóvar, Patricia A. Apellániz +3Synthetic Data Generation Generative Modeling
Information Processing and Telecommunications Center, Escuela Técnica Superior de Ingeniería de Telecomunicación, Universidad Politécnica de Madrid, Madrid, 28030, Spain · Escuela Técnica Superior de Ingeniería de Sistemas Informáticos, Universidad Politécnica de Madrid, Madrid, 28030, Spain
The Image Reconstruction Game: Drawing Common Ground Through Iterative Multimodal Dialogue
Jun 1, 2026Sherzod Hakimov, Mattia D'Agostini, Ivan Samodelkin +1VLM Evaluation Multimodal Grounding
Computational Linguistics, Department of Linguistics University of Potsdam, Germany · German Research Center for Artificial Intelligence (DFKI), Berlin, Germany
Score-Control for Hallucination Reduction in Diffusion Models
May 29, 2026Mahesh Bhosale, Naresh Kumar Devulapally, Abdul Wasi +3Score Matching Diffusion-Based Image Generation
University at Buffalo Buffalo, NY, USA
GPIC: A Giant Permissive Image Corpus for Visual Generation
May 28, 2026Keshigeyan Chandrasegaran, Kyle Sargent, Suchir Agarwal +6Image Generation Image Generation Evaluation
Stanford University · Radical Numerics · Salesforce Research +1
Rethinking FID Through the Geometry of the Reference Dataset
May 28, 2026Yunghee Lee, Byeonghyun PakImage Generation Evaluation
MaSC: A Masked Similarity Metric for Evaluating Concept-Driven Generation
May 21, 2026Patryk Bartkowiak, Lennart Petersen, Bartosz Kotrys +3Subject-Driven Image Generation Image Generation Evaluation
Adam Mickiewicz University · Kiel University · ArtCollect +1
QQJ: Quantifying Qualitative Judgment for Scalable and Human-Aligned Evaluation of Generative AI
May 17, 2026Marjan Veysi, Pirooz Shamsinejadbabaki, Mohammad Zare +1LLM-as-a-Judge Human-in-the-Loop Evaluation
AI Lab, Arioobarzan Engineering Team, Shiraz, Iran · Department of Computer Engineering and Information Technology, Shiraz University of Technology, Shiraz, Iran · Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, Genoa, Italy
One Pass Is Not Enough: Recursive Latent Refinement for Generative Models
May 14, 2026Mehdi Esmaeilzadeh, Alexia Jolicoeur-Martineau, Chirag Vashist +1Generative Modeling Image Generation Evaluation
1Simon Fraser University · 2Independent
Generative AI for Visualizing Highway Construction Hazards Through Synthetic Images and Temporal Sequences
May 11, 2026Trevor Neece, Mason Smetana, Lev KhazanovichImage Generation Autoregressive Image Generation
University of Pittsburgh, Pittsburgh, PA, USA
When Style Similarity Scores Fail: Diagnosing Raw CSD Cosine in Artist-Style Evaluation
May 9, 2026Jörg FrochtePairwise Comparison Image Generation Evaluation
Bochum University of Applied Sciences
RewardHarness: Self-Evolving Agentic Post-Training
May 9, 2026Yuxuan Zhang, Penghui Du, Bo Li +11Reward Modeling Image Editing Evaluation
University of British Columbia · Kolors Team, Kuaishou Technology · University of Waterloo +4
APEX: Assumption-free Projection-based Embedding eXamination Metric for Image Quality Assessment
May 8, 2026Caterina Gallegati, Monica Bianchini, Franco Scarselli +2Image Quality Assessment Image Generation Evaluation
University of Siena, Italy · AI for Good (AIGO), Istituto Italiano di Tecnologia, Italy · University of Verona, Italy
MIND: Monge Inception Distance for Generative Models Evaluation
May 7, 2026Quentin Berthet, Yu-Han Wu, Clement Crepy +3Image Generation Evaluation Sliced Wasserstein Distance
Google DeepMind · LPSM, Sorbonne Université

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Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment

Jiquan Yuan

School of Software and Microelectronics, Peking University, Beijing, China

Image Quality Assessment Image Generation Evaluation Knowledge Distillation

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With the rapid advancement of image generation technologies, perceptual quality assessment of AI-generated images has emerged as a crucial research direction in computer vision. The core challenge of this task lies in achieving efficient quality assessment for massive generated images. Current mainstream approaches exhibit two key limitations: 1) Methods employing complex feature extraction strategies, while improving performance, incur prohibitive computational costs that hinder real-time inference; 2) Simple image scaling-based solutions, despite their computational efficiency, demonstrate significantly inferior assessment accuracy. To address this critical issue, we propose Patch Knowledge Transfer (PKT), a knowledge distillation-based optimization framework that achieves synergistic optimization of visual representation capability and inference efficiency through an innovative multi-level knowledge transfer mechanism. Specifically, we design a dual-model architecture: a teacher model with local-global hybrid processing provides high-quality supervision signals, while a student model relying solely on global processing efficiently inherits the teacher's representation capacity through multi-level supervision. Extensive experiments conducted on 4 AIGIQA databases demonstrate that the PKT framework enables the student model to maintain performance comparable to the teacher while reducing computational costs by 67.7%. Furthermore, compared to existing methods, our approach achieves a superior balance between model efficiency and assessment accuracy.

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