3 papers
cs.CV2025
Towards Holistic Visual Quality Assessment of AI-Generated Videos: A LLM-Based Multi-Dimensional Evaluation Model
Zelu Qi, Ping Shi, Chaoyang Zhang +4
The development of AI-Generated Video (AIGV) technology has been remarkable in recent years, significantly transforming the paradigm of video content production. However, AIGVs sti…
cs.CV2025
T2VEval: Benchmark Dataset and Objective Evaluation Method for T2V-generated Videos
Zelu Qi, Ping Shi, Shuqi Wang +7
Recent advances in text-to-video (T2V) technology, as demonstrated by models such as Runway Gen-3, Pika, Sora, and Kling, have significantly broadened the applicability and popular…
cs.CV2018
Blind Predicting Similar Quality Map for Image Quality Assessment
Da Pan, Ping Shi, Ming Hou +3
A key problem in blind image quality assessment (BIQA) is how to effectively model the properties of human visual system in a data-driven manner. In this paper, we propose a simple…