14 citations · 27 across the 6 of their papers we have counts for
6 papers
SpikeRestormer: Towards Energy-Efficient All-in-One Image Restoration via Unified Event Reasoning
Shengkai Hu, Jie Shao, Jiaqi Ma +5
ANN-based All-in-One image restoration (AiOIR) unifies diverse degradation handling but incurs high computational costs, limiting its real-time deployment. While Spiking Neural Net…
ClusIR: Towards Cluster-Guided All-in-One Image Restoration
Shengkai Hu, Jiaqi Ma, Xu Zhang +3
All-in-One Image Restoration (AiOIR) aims to recover high-quality images from diverse degradations within a unified framework. However, existing methods often fail to explicitly mo…
Perceive-IR: Learning to Perceive Degradation Better for All-in-One Image Restoration
Xu Zhang, Jiaqi Ma, Guoli Wang +3
Existing All-in-One image restoration methods often fail to perceive degradation types and severity levels simultaneously, overlooking the importance of fine-grained quality percep…
HyperSIGMA: Hyperspectral Intelligence Comprehension Foundation Model
Di Wang, Meiqi Hu, Yao Jin +19
Accurate hyperspectral image (HSI) interpretation is critical for providing valuable insights into various earth observation-related applications such as urban planning, precision…
ProRes: Exploring Degradation-aware Visual Prompt for Universal Image Restoration
Jiaqi Ma, Tianheng Cheng, Guoli Wang +3
Image restoration aims to reconstruct degraded images, e.g., denoising or deblurring. Existing works focus on designing task-specific methods and there are inadequate attempts at u…
ELMformer: Efficient Raw Image Restoration with a Locally Multiplicative Transformer
Jiaqi Ma, Shengyuan Yan, Lefei Zhang +2
In order to get raw images of high quality for downstream Image Signal Process (ISP), in this paper we present an Efficient Locally Multiplicative Transformer called ELMformer for…