Large multimodal models (LMMs) have shown great results in single-image vision language
tasks. However, their abilities to solve multi-image visual language tasks is yet to be …

This paper reports on the NTIRE 2024 Quality Assessment of AI-Generated Content
Challenge which will be held in conjunction with the New Trends in Image Restoration and …

Abstract While Multimodal Large Language Models (MLLMs) have experienced significant
advancement in visual understanding and reasoning, their potential to serve as powerful …

With the rapid advancements in AI-Generated Content (AIGC) AI-Generated Images (AIGIs)
have been widely applied in entertainment education and social media. However due to the …

We introduce a Depict ed image Q uality A ssessment method (DepictQA), overcoming the
constraints of traditional score-based methods. DepictQA allows for detailed, language …

Quality assessment, which evaluates the visual quality level of multimedia experiences, has
garnered significant attention from researchers and has evolved substantially through …

Generating natural and meaningful responses to communicate with multi-modal human
inputs is a fundamental capability of Large Vision-Language Models (LVLMs). While current …

The compression of images for efficient storage and transmission is crucial in handling large
data volumes. Lossy image compression reduces storage needs but introduces perceptible …

With the development of generative models such as the diffusion model and auto-regressive
model AI-generated content (AIGC) is experiencing an explosive growth. Moreover existing …

The rapid development of Multi-modality Large Language Models (MLLMs) has navigated a
paradigm shift in computer vision, moving towards versatile foundational models. However …