13 citations · 16 across the 5 of their papers we have counts for
10 papers
Peng Cheng Object Detection Benchmark for Smart City
Yaowei Wang, Zhouxin Yang, Rui Liu +4
Object detection is an algorithm that recognizes and locates the objects in the image and has a wide range of applications in the visual understanding of complex urban scenes. Exis…
Domain Adaptation without Model Transferring
Kunhong Wu, Yucheng Shi, Yahong Han +3
In recent years, researchers have been paying increasing attention to the threats brought by deep learning models to data security and privacy, especially in the field of domain ad…
Vector-Decomposed Disentanglement for Domain-Invariant Object Detection
Aming Wu, Rui Liu, Yahong Han +2
To improve the generalization of detectors, for domain adaptive object detection (DAOD), recent advances mainly explore aligning feature-level distributions between the source and…
Exploring Uncertainty in Deep Learning for Construction of Prediction Intervals
Yuandu Lai, Yucheng Shi, Yahong Han +3
Deep learning has achieved impressive performance on many tasks in recent years. However, it has been found that it is still not enough for deep neural networks to provide only poi…
Anomaly Detection with Prototype-Guided Discriminative Latent Embeddings
Yuandu Lai, Yahong Han, Yaowei Wang
Recent efforts towards video anomaly detection (VAD) try to learn a deep autoencoder to describe normal event patterns with small reconstruction errors. The video inputs with large…
Universal-Prototype Enhancing for Few-Shot Object Detection
Aming Wu, Yahong Han, Linchao Zhu +1
Few-shot object detection (FSOD) aims to strengthen the performance of novel object detection with few labeled samples. To alleviate the constraint of few samples, enhancing the ge…