7 citations · 19 across the 6 of their papers we have counts for
6 papers
When and Where to Reset Matters for Long-Term Test-Time Adaptation
Taejun Lim, Joong-Won Hwang, Kibok Lee
When continual test-time adaptation (TTA) persists over the long term, errors accumulate in the model and further cause it to predict only a few classes for all inputs, a phenomeno…
Automated Model Evaluation for Object Detection via Prediction Consistency and Reliability
Seungju Yoo, Hyuk Kwon, Joong-Won Hwang +1
Recent advances in computer vision have made training object detectors more efficient and effective; however, assessing their performance in real-world applications still relies on…
Adversarial Training with Stochastic Weight Average
Joong-Won Hwang, Youngwan Lee, Sungchan Oh +1
Adversarial training deep neural networks often experience serious overfitting problem. Recently, it is explained that the overfitting happens because the sample complexity of trai…
Localization Uncertainty Estimation for Anchor-Free Object Detection
Youngwan Lee, Joong-won Hwang, Hyung-Il Kim +4
Since many safety-critical systems, such as surgical robots and autonomous driving cars operate in unstable environments with sensor noise and incomplete data, it is desirable for…
An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection
Youngwan Lee, Joong-won Hwang, Sangrok Lee +2
As DenseNet conserves intermediate features with diverse receptive fields by aggregating them with dense connection, it shows good performance on the object detection task. Althoug…
Rank of Experts: Detection Network Ensemble
Seung-Hwan Bae, Youngwan Lee, Youngjoo Jo +2
The recent advances of convolutional detectors show impressive performance improvement for large scale object detection. However, in general, the detection performance usually decr…