Program
Accepted papers
Accepted papers
- Incremental Learning Techniques for Semantic Segmentation, Umberto Michieli, Pietro Zanuttigh
- Multi-level Domain Adaptive learning for Cross-Domain Detection, Rongchang Xie, Fei Yu, Jiachao Wang, Yizhou Wang, Li Zhang
- Improving CNN classifiers by estimating test-time priors, Milan Sulc, Jiri Matas
- Hallucinating Agnostic Images to Generalize Across Domains, Fabio M. Carlucci, Paolo Russo, Tatiana Tommasi, Barbara Caputo
- Domain Adaptation for Vehicle Detection from Bird's Eye View LiDAR Point Cloud Data, Khaled Saleh, Ahmed Abobakr, Mohammed Attia, Julie Iskander, Darius Nahavandi, Mohammed Hossny, Saeid Nahavandi
- Towards Efficient Instance Segmentation with Hierarchical Distillation, Ziwei Deng, Quan Kong, Tomokazu Murakami
- Cross Domain Image Matching in Presence of Outliers, Xin Liu, Jan van Gemert, S. Khademi
- Unsupervised Domain Adaptation using Deep Networks with Cross-Grafted Stacks, Jinyong Hou, Xuejie Ding, Jeremiah Deng, Stephen Cranefield