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08/06/2022
Class Is Invariant to Context and Vice Versa: On Learning Invariance for Out-Of-Distribution Generalization
Out-Of-Distribution generalization (OOD) is all about learning invarianc...
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07/27/2022
Identifying Hard Noise in Long-Tailed Sample Distribution
Conventional de-noising methods rely on the assumption that all samples ...
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07/19/2022
Invariant Feature Learning for Generalized Long-Tailed Classification
Existing long-tailed classification (LT) methods only focus on tackling ...
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06/17/2021
Adversarial Visual Robustness by Causal Intervention
Adversarial training is the de facto most promising defense against adve...
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03/02/2021
Distilling Causal Effect of Data in Class-Incremental Learning
We propose a causal framework to explain the catastrophic forgetting in ...
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09/28/2020
Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect
As the class size grows, maintaining a balanced dataset across many clas...
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04/02/2020
Learning to Segment the Tail
Real-world visual recognition requires handling the extreme sample imbal...
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02/27/2020
Unbiased Scene Graph Generation from Biased Training
Today's scene graph generation (SGG) task is still far from practical, m...
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12/06/2018
Auto-Encoding Graphical Inductive Bias for Descriptive Image Captioning
We propose Scene Graph Auto-Encoder (SGAE) that incorporates the languag...
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12/06/2018
Auto-Encoding Scene Graphs for Image Captioning
We propose Scene Graph Auto-Encoder (SGAE) that incorporates the languag...
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12/05/2018