Search Results for author: Naiyang Guan

Found 5 papers, 0 papers with code

MVP: Meta Visual Prompt Tuning for Few-Shot Remote Sensing Image Scene Classification

no code implementations17 Sep 2023 Junjie Zhu, Yiying Li, Chunping Qiu, Ke Yang, Naiyang Guan, Xiaodong Yi

In order to tackle these issues, we turn to the recently proposed parameter-efficient tuning methods, such as VPT, which updates only the newly added prompt parameters while keeping the pre-trained backbone frozen.

Data Augmentation Domain Adaptation +3

PVP: Pre-trained Visual Parameter-Efficient Tuning

no code implementations26 Apr 2023 Zhao Song, Ke Yang, Naiyang Guan, Junjie Zhu, Peng Qiao, Qingyong Hu

Large-scale pre-trained transformers have demonstrated remarkable success in various computer vision tasks.

Ranked #4 on Image Classification on VTAB-1k (using extra training data)

Fine-Grained Image Classification

Truncated Cauchy Non-negative Matrix Factorization

no code implementations2 Jun 2019 Naiyang Guan, Tongliang Liu, Yangmuzi Zhang, DaCheng Tao, Larry S. Davis

Non-negative matrix factorization (NMF) minimizes the Euclidean distance between the data matrix and its low rank approximation, and it fails when applied to corrupted data because the loss function is sensitive to outliers.

Clustering Image Clustering

MahNMF: Manhattan Non-negative Matrix Factorization

no code implementations14 Jul 2012 Naiyang Guan, DaCheng Tao, Zhigang Luo, John Shawe-Taylor

This paper presents Manhattan NMF (MahNMF) which minimizes the Manhattan distance between $X$ and $W^T H$ for modeling the heavy tailed Laplacian noise.

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