30 citations · 141 across the 17 of their papers we have counts for
36 papers
Domain Adaptor Networks for Hyperspectral Image Recognition
Gustavo Perez, Subhransu Maji
We consider the problem of adapting a network trained on three-channel color images to a hyperspectral domain with a large number of channels. To this end, we propose domain adapto…
The Semi-Supervised iNaturalist Challenge at the FGVC8 Workshop
Jong-Chyi Su, Subhransu Maji
Semi-iNat is a challenging dataset for semi-supervised classification with a long-tailed distribution of classes, fine-grained categories, and domain shifts between labeled and unl…
A Realistic Evaluation of Semi-Supervised Learning for Fine-Grained Classification
Jong-Chyi Su, Zezhou Cheng, Subhransu Maji
We evaluate the effectiveness of semi-supervised learning (SSL) on a realistic benchmark where data exhibits considerable class imbalance and contains images from novel classes. Ou…
The Semi-Supervised iNaturalist-Aves Challenge at FGVC7 Workshop
Jong-Chyi Su, Subhransu Maji
This document describes the details and the motivation behind a new dataset we collected for the semi-supervised recognition challenge~\cite{semi-aves} at the FGVC7 workshop at CVP…
Supervised Momentum Contrastive Learning for Few-Shot Classification
Orchid Majumder, Avinash Ravichandran, Subhransu Maji +3
Few-shot learning aims to transfer information from one task to enable generalization on novel tasks given a few examples. This information is present both in the domain and the cl…
Exponential Moving Average Normalization for Self-supervised and Semi-supervised Learning
Zhaowei Cai, Avinash Ravichandran, Subhransu Maji +3
We present a plug-in replacement for batch normalization (BN) called exponential moving average normalization (EMAN), which improves the performance of existing student-teacher bas…