49 citations · 50 across the 6 of their papers we have counts for
6 papers
Local Background Features Matter in Out-of-Distribution Detection
Jinlun Ye, Zhuohao Sun, Yiqiao Qiu +3
Out-of-distribution (OOD) detection is crucial when deploying deep neural networks in the real world to ensure the reliability and safety of their applications. One main challenge…
Class Incremental Learning with Task-Specific Batch Normalization and Out-of-Distribution Detection
Zhiping Zhou, Xuchen Xie, Yiqiao Qiu +3
This study focuses on incremental learning for image classification, exploring how to reduce catastrophic forgetting of all learned knowledge when access to old data is restricted.…
Anything in Any Scene: Photorealistic Video Object Insertion
Chen Bai, Zeman Shao, Guoxiang Zhang +11
Realistic video simulation has shown significant potential across diverse applications, from virtual reality to film production. This is particularly true for scenarios where captu…
Classifier-head Informed Feature Masking and Prototype-based Logit Smoothing for Out-of-Distribution Detection
Zhuohao Sun, Yiqiao Qiu, Zhijun Tan +2
Out-of-distribution (OOD) detection is essential when deploying neural networks in the real world. One main challenge is that neural networks often make overconfident predictions o…
SATS: Self-Attention Transfer for Continual Semantic Segmentation
Yiqiao Qiu, Yixing Shen, Zhuohao Sun +4
Continually learning to segment more and more types of image regions is a desired capability for many intelligent systems. However, such continual semantic segmentation suffers fro…
Topic Driven Adaptive Network for Cross-Domain Sentiment Classification
Yicheng Zhu, Yiqiao Qiu, Qingyuan Wu +2
Cross-domain sentiment classification has been a hot spot these years, which aims to learn a reliable classifier using labeled data from a source domain and evaluate it on a target…