6 citations · 16 across the 12 of their papers we have counts for
4 papers · 1 filter
Object Discovery via Contrastive Learning for Weakly Supervised Object Detection
Jinhwan Seo, Wonho Bae, Danica J. Sutherland +2
Weakly Supervised Object Detection (WSOD) is a task that detects objects in an image using a model trained only on image-level annotations. Current state-of-the-art models benefit…
Making Look-Ahead Active Learning Strategies Feasible with Neural Tangent Kernels
Mohamad Amin Mohamadi, Wonho Bae, Danica J. Sutherland
We propose a new method for approximating active learning acquisition strategies that are based on retraining with hypothetically-labeled candidate data points. Although this is us…
A Fast, Well-Founded Approximation to the Empirical Neural Tangent Kernel
Mohamad Amin Mohamadi, Wonho Bae, Danica J. Sutherland
Empirical neural tangent kernels (eNTKs) can provide a good understanding of a given network's representation: they are often far less expensive to compute and applicable more broa…
One Weird Trick to Improve Your Semi-Weakly Supervised Semantic Segmentation Model
Wonho Bae, Junhyug Noh, Milad Jalali Asadabadi +1
Semi-weakly supervised semantic segmentation (SWSSS) aims to train a model to identify objects in images based on a small number of images with pixel-level labels, and many more im…