6 citations · 8 across the 8 of their papers we have counts for
4 papers · 1 filter
Grounding-IQA: Grounding Multimodal Language Model for Image Quality Assessment
Zheng Chen, Xun Zhang, Wenbo Li +7
The development of multimodal large language models (MLLMs) enables the evaluation of image quality through natural language descriptions. This advancement allows for more detailed…
Unleashing the Power of One-Step Diffusion based Image Super-Resolution via a Large-Scale Diffusion Discriminator
Jianze Li, Jiezhang Cao, Zichen Zou +5
Diffusion models have demonstrated excellent performance for real-world image super-resolution (Real-ISR), albeit at high computational costs. Most existing methods are trying to d…
2DQuant: Low-bit Post-Training Quantization for Image Super-Resolution
Kai Liu, Haotong Qin, Yong Guo +4
Low-bit quantization has become widespread for compressing image super-resolution (SR) models for edge deployment, which allows advanced SR models to enjoy compact low-bit paramete…
Binarized Diffusion Model for Image Super-Resolution
Zheng Chen, Haotong Qin, Yong Guo +4
Advanced diffusion models (DMs) perform impressively in image super-resolution (SR), but the high memory and computational costs hinder their deployment. Binarization, an ultra-com…