Deep Unsupervised Hashing with Latent Semantic Components

no code implementations • 17 Mar 2022 • Qinghong Lin, Xiaojun Chen, Qin Zhang, Shaotian Cai, Wenzhe Zhao, Hongfa Wang

Firstly, DSCH constructs a semantic component structure by uncovering the fine-grained semantics components of images with a Gaussian Mixture Modal~(GMM), where an image is represented as a mixture of multiple components, and the semantics co-occurrence are exploited.

Common Sense Reasoning Image Retrieval +1

Deep Self-Adaptive Hashing for Image Retrieval

no code implementations • 16 Aug 2021 • Qinghong Lin, Xiaojun Chen, Qin Zhang, Shangxuan Tian, Yudong Chen

Secondly, we measure the priorities of data pairs with PIC and assign adaptive weights to them, which is relies on the assumption that more dissimilar data pairs contain more discriminative information for hash learning.

Deep Hashing Image Retrieval

Deep Superpixel Cut for Unsupervised Image Segmentation

no code implementations • 10 Mar 2021 • Qinghong Lin, Weichan Zhong, Jianglin Lu

Most of the early algorithms are unsupervised methods, which use hand-crafted features to divide the image into many regions.

Clustering Image Segmentation +4