9 papers · 1 filter
Hidden Meanings in Plain Sight: RebusBench for Evaluating Cognitive Visual Reasoning
Seyed Amir Kasaei, Arash Marioriyad, Mahbod Khaleti +3
Large Vision-Language Models (LVLMs) have achieved remarkable proficiency in explicit visual recognition, effectively describing what is directly visible in an image. However, a cr…
Infinity and Beyond: Compositional Alignment in VAR and Diffusion T2I Models
Hossein Shahabadi, Niki Sepasian, Arash Marioriyad +2
Achieving compositional alignment between textual descriptions and generated images - covering objects, attributes, and spatial relationships - remains a core challenge for modern…
No Concept Left Behind: Test-Time Optimization for Compositional Text-to-Image Generation
Mohammad Hossein Sameti, Amir M. Mansourian, Arash Marioriyad +3
Despite recent advances in text-to-image (T2I) models, they often fail to faithfully render all elements of complex prompts, frequently omitting or misrepresenting specific objects…
Evaluating the Evaluators: Metrics for Compositional Text-to-Image Generation
Seyed Amir Kasaei, Ali Aghayari, Arash Marioriyad +4
Text-image generation has advanced rapidly, but assessing whether outputs truly capture the objects, attributes, and relations described in prompts remains a central challenge. Eva…
CARINOX: Inference-time Scaling with Category-Aware Reward-based Initial Noise Optimization and Exploration
Seyed Amir Kasaei, Ali Aghayari, Arash Marioriyad +5
Text-to-image diffusion models, such as Stable Diffusion, can produce high-quality and diverse images but often fail to achieve compositional alignment, particularly when prompts d…
Why Settle for Mid: A Probabilistic Viewpoint to Spatial Relationship Alignment in Text-to-image Models
Parham Rezaei, Arash Marioriyad, Mahdieh Soleymani Baghshah +1
Despite the ability of text-to-image models to generate high-quality, realistic, and diverse images, they face challenges in compositional generation, often struggling to accuratel…
Diffusion Beats Autoregressive: An Evaluation of Compositional Generation in Text-to-Image Models
Arash Marioriyad, Parham Rezaei, Mahdieh Soleymani Baghshah +1
Text-to-image (T2I) generative models, such as Stable Diffusion and DALL-E, have shown remarkable proficiency in producing high-quality, realistic, and natural images from textual…
Attention Overlap Is Responsible for The Entity Missing Problem in Text-to-image Diffusion Models!
Arash Marioriyad, Mohammadali Banayeeanzade, Reza Abbasi +2
Text-to-image diffusion models, such as Stable Diffusion and DALL-E, are capable of generating high-quality, diverse, and realistic images from textual prompts. However, they somet…
GABInsight: Exploring Gender-Activity Binding Bias in Vision-Language Models
Ali Abdollahi, Mahdi Ghaznavi, Mohammad Reza Karimi Nejad +6
Vision-language models (VLMs) are intensively used in many downstream tasks, including those requiring assessments of individuals appearing in the images. While VLMs perform well i…