63 citations · 87 across the 12 of their papers we have counts for
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cs.CV2022
Rethinking Few-Shot Object Detection on a Multi-Domain Benchmark
Kibok Lee, Hao Yang, Satyaki Chakraborty +4
Most existing works on few-shot object detection (FSOD) focus on a setting where both pre-training and few-shot learning datasets are from a similar domain. However, few-shot algor…
cs.CV2022★ 2 cited
Omni-DETR: Omni-Supervised Object Detection with Transformers
Pei Wang, Zhaowei Cai, Hao Yang +4
We consider the problem of omni-supervised object detection, which can use unlabeled, fully labeled and weakly labeled annotations, such as image tags, counts, points, etc., for ob…
cs.LG2022★ 3 cited
Rethinking Feature Uncertainty in Stochastic Neural Networks for Adversarial Robustness
Hao Yang, Min Wang, Zhengfei Yu +1
It is well-known that deep neural networks (DNNs) have shown remarkable success in many fields. However, when adding an imperceptible magnitude perturbation on the model input, the…