20 citations · 53 across the 7 of their papers we have counts for
4 papers · 1 filter
Contrastive Visual-Linguistic Pretraining
Lei Shi, Kai Shuang, Shijie Geng +6
Several multi-modality representation learning approaches such as LXMERT and ViLBERT have been proposed recently. Such approaches can achieve superior performance due to the high-l…
Gradient Regularized Contrastive Learning for Continual Domain Adaptation
Peng Su, Shixiang Tang, Peng Gao +3
Human beings can quickly adapt to environmental changes by leveraging learning experience. However, the poor ability of adapting to dynamic environments remains a major challenge f…
Modal Uncertainty Estimation via Discrete Latent Representation
Di Qiu, Lok Ming Lui
Many important problems in the real world don't have unique solutions. It is thus important for machine learning models to be capable of proposing different plausible solutions wit…
Adapting Object Detectors with Conditional Domain Normalization
Peng Su, Kun Wang, Xingyu Zeng +4
Real-world object detectors are often challenged by the domain gaps between different datasets. In this work, we present the Conditional Domain Normalization (CDN) to bridge the do…