70 citations · 156 across the 14 of their papers we have counts for
15 papers · 1 filter
Pixel Adaptive Deep Unfolding Transformer for Hyperspectral Image Reconstruction
Miaoyu Li, Ying Fu, Ji Liu +1
Hyperspectral Image (HSI) reconstruction has made gratifying progress with the deep unfolding framework by formulating the problem into a data module and a prior module. Neverthele…
Spectral Enhanced Rectangle Transformer for Hyperspectral Image Denoising
Miaoyu Li, Ji Liu, Ying Fu +2
Denoising is a crucial step for hyperspectral image (HSI) applications. Though witnessing the great power of deep learning, existing HSI denoising methods suffer from limitations i…
LG-BPN: Local and Global Blind-Patch Network for Self-Supervised Real-World Denoising
Zichun Wang, Ying Fu, Ji Liu +1
Despite the significant results on synthetic noise under simplified assumptions, most self-supervised denoising methods fail under real noise due to the strong spatial noise correl…
Instance Segmentation in the Dark
Linwei Chen, Ying Fu, Kaixuan Wei +2
Existing instance segmentation techniques are primarily tailored for high-visibility inputs, but their performance significantly deteriorates in extremely low-light environments. I…
Spatial-Spectral Transformer for Hyperspectral Image Denoising
Miaoyu Li, Ying Fu, Yulun Zhang
Hyperspectral image (HSI) denoising is a crucial preprocessing procedure for the subsequent HSI applications. Unfortunately, though witnessing the development of deep learning in H…
ProbNVS: Fast Novel View Synthesis with Learned Probability-Guided Sampling
Yuemei Zhou, Tao Yu, Zerong Zheng +2
Existing state-of-the-art novel view synthesis methods rely on either fairly accurate 3D geometry estimation or sampling of the entire space for neural volumetric rendering, which…