3 papers
cs.CV2023
SR-init: An interpretable layer pruning method
Hui Tang, Yao Lu, Qi Xuan
Despite the popularization of deep neural networks (DNNs) in many fields, it is still challenging to deploy state-of-the-art models to resource-constrained devices due to high comp…
cs.CV2023
A New Benchmark: On the Utility of Synthetic Data with Blender for Bare Supervised Learning and Downstream Domain Adaptation
Hui Tang, Kui Jia
Deep learning in computer vision has achieved great success with the price of large-scale labeled training data. However, exhaustive data annotation is impracticable for each task…
cs.CV2023
Unsupervised Domain Adaptation via Distilled Discriminative Clustering
Hui Tang, Yaowei Wang, Kui Jia
Unsupervised domain adaptation addresses the problem of classifying data in an unlabeled target domain, given labeled source domain data that share a common label space but follow…