no code implementations • 29 Jan 2023 • Beier Zhu, Yulei Niu, Saeil Lee, Minhoe Hur, Hanwang Zhang
We present a new paradigm for fine-tuning large-scale visionlanguage pre-trained models on downstream task, dubbed Prompt Regularization (ProReg).
1 code implementation • ICCV 2023 • Ze Yang, Ruibo Li, Evan Ling, Chi Zhang, Yiming Wang, Dezhao Huang, Keng Teck Ma, Minhoe Hur, Guosheng Lin
To address this issue, we propose a new label-guided knowledge distillation (LGKD) loss, where the old model output is expanded and transplanted (with the guidance of the ground truth label) to form a semantically appropriate class correspondence with the new model output.
Ranked #1 on Continual Semantic Segmentation on ScanNet
1 code implementation • 7 Oct 2022 • Evan Ling, Dezhao Huang, Minhoe Hur
In our work, we propose a simple yet effective data-centric approach, Occlusion Copy & Paste, to introduce occluded examples to models during training - we tailor the general copy & paste augmentation approach to tackle the difficult problem of same-class occlusion.
1 code implementation • 18 Jun 2020 • Changhwa Park, Jonghyun Lee, Jaeyoon Yoo, Minhoe Hur, Sungroh Yoon
Enhancing feature transferability by matching marginal distributions has led to improvements in domain adaptation, although this is at the expense of feature discrimination.