277 citations · 1.7k across the 70 of their papers we have counts for
6 papers · 1 filter
Label-Efficient Object Detection via Region Proposal Network Pre-Training
Nanqing Dong, Linus Ericsson, Yongxin Yang +2
Self-supervised pre-training, based on the pretext task of instance discrimination, has fueled the recent advance in label-efficient object detection. However, existing studies foc…
ZooD: Exploiting Model Zoo for Out-of-Distribution Generalization
Qishi Dong, Awais Muhammad, Fengwei Zhou +5
Recent advances on large-scale pre-training have shown great potentials of leveraging a large set of Pre-Trained Models (PTMs) for improving Out-of-Distribution (OoD) generalizatio…
MEDFAIR: Benchmarking Fairness for Medical Imaging
Yongshuo Zong, Yongxin Yang, Timothy Hospedales
A multitude of work has shown that machine learning-based medical diagnosis systems can be biased against certain subgroups of people. This has motivated a growing number of bias m…
Fine-Grained VR Sketching: Dataset and Insights
Ling Luo, Yulia Gryaditskaya, Yongxin Yang +2
We present the first fine-grained dataset of 1,497 3D VR sketch and 3D shape pairs of a chair category with large shapes diversity. Our dataset supports the recent trend in the ske…
Towards 3D VR-Sketch to 3D Shape Retrieval
Ling Luo, Yulia Gryaditskaya, Yongxin Yang +2
Growing free online 3D shapes collections dictated research on 3D retrieval. Active debate has however been had on (i) what the best input modality is to trigger retrieval, and (ii…
Batch-Ensemble Stochastic Neural Networks for Out-of-Distribution Detection
Xiongjie Chen, Yunpeng Li, Yongxin Yang
Out-of-distribution (OOD) detection has recently received much attention from the machine learning community due to its importance in deploying machine learning models in real-worl…