84 citations · 129 across the 9 of their papers we have counts for
8 papers · 1 filter
Semantic Compositional Learning for Low-shot Scene Graph Generation
Tao He, Lianli Gao, Jingkuan Song +2
Scene graphs provide valuable information to many downstream tasks. Many scene graph generation (SGG) models solely use the limited annotated relation triples for training, leading…
Exploiting Scene Graphs for Human-Object Interaction Detection
Tao He, Lianli Gao, Jingkuan Song +1
Human-Object Interaction (HOI) detection is a fundamental visual task aiming at localizing and recognizing interactions between humans and objects. Existing works focus on the visu…
Learning from the Scene and Borrowing from the Rich: Tackling the Long Tail in Scene Graph Generation
Tao He, Lianli Gao, Jingkuan Song +2
Despite the huge progress in scene graph generation in recent years, its long-tail distribution in object relationships remains a challenging and pestering issue. Existing methods…
One Network for Multi-Domains: Domain Adaptive Hashing with Intersectant Generative Adversarial Network
Tao He, Yuan-Fang Li, Lianli Gao +2
With the recent explosive increase of digital data, image recognition and retrieval become a critical practical application. Hashing is an effective solution to this problem, due t…
Understanding the Mechanism of Deep Learning Framework for Lesion Detection in Pathological Images with Breast Cancer
Wei-Wen Hsu, Chung-Hao Chen, Chang Hoa +7
The computer-aided detection (CADe) systems are developed to assist pathologists in slide assessment, increasing diagnosis efficiency and reducing missing inspections. Many studies…
Binary Generative Adversarial Networks for Image Retrieval
Jingkuan Song
The most striking successes in image retrieval using deep hashing have mostly involved discriminative models, which require labels. In this paper, we use binary generative adversar…