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07/14/2023
Improved Flood Insights: Diffusion-Based SAR to EO Image Translation
Driven by rapid climate change, the frequency and intensity of flood eve...
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03/26/2023
VisDA 2022 Challenge: Domain Adaptation for Industrial Waste Sorting
Label-efficient and reliable semantic segmentation is essential for many...
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03/21/2023
CAFS: Class Adaptive Framework for Semi-Supervised Semantic Segmentation
Semi-supervised semantic segmentation learns a model for classifying pix...
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03/17/2023
Bidirectional Domain Mixup for Domain Adaptive Semantic Segmentation
Mixup provides interpolated training samples and allows the model to obt...
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03/14/2023
Implicit Stacked Autoregressive Model for Video Prediction
Future frame prediction has been approached through two primary methods:...
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03/08/2023
Intermediate and Future Frame Prediction of Geostationary Satellite Imagery With Warp and Refine Network
Geostationary satellite imagery has applications in climate and weather ...
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12/20/2022
Self-Pair: Synthesizing Changes from Single Source for Object Change Detection in Remote Sensing Imagery
For change detection in remote sensing, constructing a training dataset ...
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12/06/2022
Domain Generalization Strategy to Train Classifiers Robust to Spatial-Temporal Shift
Deep learning-based weather prediction models have advanced significantl...
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12/06/2022
Simple Baseline for Weather Forecasting Using Spatiotemporal Context Aggregation Network
Traditional weather forecasting relies on domain expertise and computati...
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11/26/2022
1st Place Solution to NeurIPS 2022 Challenge on Visual Domain Adaptation
The Visual Domain Adaptation(VisDA) 2022 Challenge calls for an unsuperv...
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04/30/2022
Source Domain Subset Sampling for Semi-Supervised Domain Adaptation in Semantic Segmentation
In this paper, we introduce source domain subset sampling (SDSS) as a ne...
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04/04/2022
Unsupervised Change Detection Based on Image Reconstruction Loss
To train the change detector, bi-temporal images taken at different time...
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01/19/2022
Using Self-Supervised Pretext Tasks for Active Learning
Labeling a large set of data is expensive. Active learning aims to tackl...
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08/10/2021
Exploiting Features with Split-and-Share Module
Deep convolutional neural networks (CNNs) have shown state-of-the-art pe...
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06/21/2020
