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Junmin Liu

3 accepted papers

2026

Towards Understanding The Calibration Benefits of Sharpness-Aware Minimization

ICLR 2026poster

Deep neural networks have been increasingly used in safety-critical applications such as medical diagnosis and autonomous driving. However, many studies suggest that they are prone to being poorly calibrated and have a propensity for overconfidence, which may have disastrous consequences. In this pa…

Cited by 0SourceScholar
2021

Deep Gradient Projection Networks for Pan-sharpening

CVPR 2021poster

Pan-sharpening is an important technique for remote sensing imaging systems to obtain high resolution multispectral images. Recently, deep learning has become the most popular tool for pan-sharpening. This paper develops a model-based deep pan-sharpening approach. Specifically, two optimization prob…

Cited by 194PDFcodeScholar
2020

DIDFuse: Deep Image Decomposition for Infrared and Visible Image Fusion

IJCAI 2020poster

Infrared and visible image fusion, a hot topic in the field of image processing, aims at obtaining fused images keeping the advantages of source images. This paper proposes a novel auto-encoder (AE) based fusion network. The core idea is that the encoder decomposes an image into background and detai…