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Found 5 papers, 2 papers with code
Human-Activity AGV Quality Assessment: A Benchmark Dataset and an Objective Evaluation Metric
To address this challenge, we conduct a pioneering study on human activity AGV quality assessment, focusing on visual quality evaluation and the identification of semantic distortions.
LMM-VQA: Advancing Video Quality Assessment with Large Multimodal Models
Then, we design a spatiotemporal vision encoder to extract spatial and temporal features to represent the quality characteristics of videos, which are subsequently mapped into the language space by the spatiotemporal projector for modality alignment.
Dual-Branch Network for Portrait Image Quality Assessment
We employ the fidelity loss to train the model via a learning-to-rank manner to mitigate inconsistencies in quality scores in the portrait image quality assessment dataset PIQ.
Q-Boost: On Visual Quality Assessment Ability of Low-level Multi-Modality Foundation Models
Recent advancements in Multi-modality Large Language Models (MLLMs) have demonstrated remarkable capabilities in complex high-level vision tasks.
Exploring the Naturalness of AI-Generated Images
In this paper, we take the first step to benchmark and assess the visual naturalness of AI-generated images.
