21 citations · 58 across the 8 of their papers we have counts for
7 papers · 1 filter
Unlocking Zero-Shot Geospatial Reasoning via Indirect Rewards
Chenhui Xu, Fuxun Yu, Michael J. Bianco +15
Training robust reasoning vision-language models (VLMs) in rare domains (such as geospatial) is fundamentally constrained by supervision scarcity. While raw geospatial imagery is a…
Geospatial Foundational Embedder: Top-1 Winning Solution on EarthVision Embed2Scale Challenge (CVPR 2025)
Zirui Xu, Raphael Tang, Mike Bianco +4
EarthVision Embed2Scale challenge (CVPR 2025) aims to develop foundational geospatial models to embed SSL4EO-S12 hyperspectral geospatial data cubes into embedding vectors that fac…
Online Learning via Memory: Retrieval-Augmented Detector Adaptation
Yanan Jian, Fuxun Yu, Qi Zhang +3
This paper presents a novel way of online adapting any off-the-shelf object detection model to a novel domain without retraining the detector model. Inspired by how humans quickly…
HyperSTAR: Task-Aware Hyperparameters for Deep Networks
Gaurav Mittal, Chang Liu, Nikolaos Karianakis +3
While deep neural networks excel in solving visual recognition tasks, they require significant effort to find hyperparameters that make them work optimally. Hyperparameter Optimiza…
Unsupervised Domain Adaptation for Object Detection via Cross-Domain Semi-Supervised Learning
Fuxun Yu, Di Wang, Yinpeng Chen +7
Current state-of-the-art object detectors can have significant performance drop when deployed in the wild due to domain gaps with training data. Unsupervised Domain Adaptation (UDA…
Reinforced Temporal Attention and Split-Rate Transfer for Depth-Based Person Re-Identification
Nikolaos Karianakis, Zicheng Liu, Yinpeng Chen +1
We address the problem of person re-identification from commodity depth sensors. One challenge for depth-based recognition is data scarcity. Our first contribution addresses this p…