2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CV2025
RUNA: Object-level Out-of-Distribution Detection via Regional Uncertainty Alignment of Multimodal Representations
Bin Zhang, Jinggang Chen, Xiaoyang Qu +5
Enabling object detectors to recognize out-of-distribution (OOD) objects is vital for building reliable systems. A primary obstacle stems from the fact that models frequently do no…
cs.LG2023★ 2 cited
GAIA: Delving into Gradient-based Attribution Abnormality for Out-of-distribution Detection
Jinggang Chen, Junjie Li, Xiaoyang Qu +3
Detecting out-of-distribution (OOD) examples is crucial to guarantee the reliability and safety of deep neural networks in real-world settings. In this paper, we offer an innovativ…
cs.LG2023
Detecting Out-of-distribution Examples via Class-conditional Impressions Reappearing
Jinggang Chen, Xiaoyang Qu, Junjie Li +3
Out-of-distribution (OOD) detection aims at enhancing standard deep neural networks to distinguish anomalous inputs from original training data. Previous progress has introduced va…