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Found 7 papers, 3 papers with code
Person Re-ID through Unsupervised Hypergraph Rank Selection and Fusion
Person Re-ID has been gaining a lot of attention and nowadays is of fundamental importance in many camera surveillance applications.
Graph Convolutional Networks based on Manifold Learning for Semi-Supervised Image Classification
In spite of many advances, most of the approaches require a large amount of labeled data, which is often not available, due to costs and difficulties of manual labeling processes.
Rank Flow Embedding for Unsupervised and Semi-Supervised Manifold Learning
High effective results demonstrate the effectiveness of the proposed method on different tasks: unsupervised image retrieval, semi-supervised classification, and person Re-ID.
Improving Transferability of Domain Adaptation Networks Through Domain Alignment Layers
Deep learning (DL) has been the primary approach used in various computer vision tasks due to its relevant results achieved on many tasks.
Multi-Source Unsupervised Domain Adaptation
Unsupervised Domain Adaptation
Multimedia Retrieval Through Unsupervised Hypergraph-Based Manifold Ranking
In this paper, a novel manifold ranking algorithm is proposed based on the hypergraphs for unsupervised multimedia retrieval tasks.
Unsupervised Graph-based Rank Aggregation for Improved Retrieval
This paper presents a robust and comprehensive graph-based rank aggregation approach, used to combine results of isolated ranker models in retrieval tasks.
