Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial Representation Learning

no code implementations • ICCV 2023 • Colorado J. Reed, Ritwik Gupta, Shufan Li, Sarah Brockman, Christopher Funk, Brian Clipp, Kurt Keutzer, Salvatore Candido, Matt Uyttendaele, Trevor Darrell

Large, pretrained models are commonly finetuned with imagery that is heavily augmented to mimic different conditions and scales, with the resulting models used for various tasks with imagery from a range of spatial scales.

Representation Learning

xFBD: Focused Building Damage Dataset and Analysis

no code implementations • 23 Dec 2022 • Dennis Melamed, Cameron Johnson, Chen Zhao, Russell Blue, Philip Morrone, Anthony Hoogs, Brian Clipp

This new challenge involves a new dataset and metrics indicating solution performance when damage is more local and limited than in xBD.

MEVID: Multi-view Extended Videos with Identities for Video Person Re-Identification

1 code implementation • 9 Nov 2022 • Daniel Davila, Dawei Du, Bryon Lewis, Christopher Funk, Joseph Van Pelt, Roderick Collins, Kellie Corona, Matt Brown, Scott McCloskey, Anthony Hoogs, Brian Clipp

In this paper, we present the Multi-view Extended Videos with Identities (MEVID) dataset for large-scale, video person re-identification (ReID) in the wild.

Multi-Object Tracking object-detection +3

Cascade Transformers for End-to-End Person Search

1 code implementation • CVPR 2022 • Rui Yu, Dawei Du, Rodney LaLonde, Daniel Davila, Christopher Funk, Anthony Hoogs, Brian Clipp

In this paper, we propose the Cascade Occluded Attention Transformer (COAT) for end-to-end person search.

Human Detection Person Search