3 papers
eess.IV2025
CLIPPan: Adapting CLIP as A Supervisor for Unsupervised Pansharpening
Lihua Jian, Jiabo Liu, Shaowu Wu +1
Despite remarkable advancements in supervised pansharpening neural networks, these methods face domain adaptation challenges of resolution due to the intrinsic disparity between si…
eess.IV2024
EigenSR: Eigenimage-Bridged Pre-Trained RGB Learners for Single Hyperspectral Image Super-Resolution
Xi Su, Xiangfei Shen, Mingyang Wan +4
Single hyperspectral image super-resolution (single-HSI-SR) aims to improve the resolution of a single input low-resolution HSI. Due to the bottleneck of data scarcity, the develop…
cs.CV2024
Progressive Fine-to-Coarse Reconstruction for Accurate Low-Bit Post-Training Quantization in Vision Transformers
Rui Ding, Liang Yong, Sihuan Zhao +4
Due to its efficiency, Post-Training Quantization (PTQ) has been widely adopted for compressing Vision Transformers (ViTs). However, when quantized into low-bit representations, th…