266 citations
- Queensland University of TechnologyAU7 papers
- Australian National UniversityAU5 papers
- Commonwealth Scientific and Industrial Research OrganisationAU5 papers
- Data61AU5 papers
- Australian Centre for Robotic VisionAU4 papers
- The University of SydneyAU2 papers
- Baidu (China)CN1 paper
- Centre National de la Recherche ScientifiqueFR1 paper
- Chinese University of Hong KongHK1 paper
- Drexel UniversityUS1 paper
- Institut Universitaire de FranceFR1 paper
- James Cook UniversityAU1 paper
4 papers · 1 filter
Localising In Complex Scenes Using Balanced Adversarial Adaptation
Gil Avraham, Yan Zuo, Tom Drummond
Domain adaptation and generative modelling have collectively mitigated the expensive nature of data collection and labelling by leveraging the rich abundance of accurate, labelled…
Channel Attention based Iterative Residual Learning for Depth Map Super-Resolution
Xibin Song, Yuchao Dai, Dingfu Zhou +4
Despite the remarkable progresses made in deep-learning based depth map super-resolution (DSR), how to tackle real-world degradation in low-resolution (LR) depth maps remains a maj…
Equalization Loss for Long-Tailed Object Recognition
Jingru Tan, Changbao Wang, Buyu Li +4
Object recognition techniques using convolutional neural networks (CNN) have achieved great success. However, state-of-the-art object detection methods still perform poorly on larg…
EcoNAS: Finding Proxies for Economical Neural Architecture Search
Dongzhan Zhou, Xinchi Zhou, Wenwei Zhang +4
Neural Architecture Search (NAS) achieves significant progress in many computer vision tasks. While many methods have been proposed to improve the efficiency of NAS, the search pro…