Chunhua Shen

An Embarrassingly Simple Approach to Visual Domain Adaptation

2018 · IEEE Transactions on Image Processing

We show that it is possible to achieve high-quality domain adaptation without explicit adaptation. The nature of the classification problem means that when samples from the same class in different domains are sufficiently close, and …

To Balance or Not to Balance: An Embarrassingly Simple Approach for Learning with Long-Tailed Distributions.

2019 · arXiv (Cornell University)

Real-world visual data often exhibits a long-tailed distribution, where some ''head'' classes have a large number of samples, yet only a few samples are available for ''tail'' classes. Such imbalanced distribution causes a great challenge …

DeepEMD: Differentiable Earth Mover's Distance for Few-Shot Learning

2022 · IEEE Transactions on Pattern Analysis and Machine Intelligence

In this work, we develop methods for few-shot image classification from a new perspective of optimal matching between image regions. We employ the Earth Mover's Distance (EMD) as a metric to compute a structural distance …

FoPro: Few-Shot Guided Robust Webly-Supervised Prototypical Learning

2022 · arXiv (Cornell University)

Recently, webly supervised learning (WSL) has been studied to leverage numerous and accessible data from the Internet. Most existing methods focus on learning noise-robust models from web images while neglecting the performance drop caused by …