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04/10/2023
Video-kMaX: A Simple Unified Approach for Online and Near-Online Video Panoptic Segmentation
Video Panoptic Segmentation (VPS) aims to achieve comprehensive pixel-le...
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03/29/2023
TTA-COPE: Test-Time Adaptation for Category-Level Object Pose Estimation
Test-time adaptation methods have been gaining attention recently as a p...
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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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12/16/2022
CD-TTA: Compound Domain Test-time Adaptation for Semantic Segmentation
Test-time adaptation (TTA) has attracted significant attention due to it...
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12/16/2022
Learning Classifiers of Prototypes and Reciprocal Points for Universal Domain Adaptation
Universal Domain Adaptation aims to transfer the knowledge between the d...
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11/21/2022
MATE: Masked Autoencoders are Online 3D Test-Time Learners
We propose MATE, the first Test-Time-Training (TTT) method designed for ...
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09/13/2022
Moving from 2D to 3D: volumetric medical image classification for rectal cancer staging
Volumetric images from Magnetic Resonance Imaging (MRI) provide invaluab...
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11/24/2021
UDA-COPE: Unsupervised Domain Adaptation for Category-level Object Pose Estimation
Learning to estimate object pose often requires ground-truth (GT) labels...
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10/08/2021
Discover, Hallucinate, and Adapt: Open Compound Domain Adaptation for Semantic Segmentation
Unsupervised domain adaptation (UDA) for semantic segmentation has been ...
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08/12/2021
LabOR: Labeling Only if Required for Domain Adaptive Semantic Segmentation
Unsupervised Domain Adaptation (UDA) for semantic segmentation has been ...
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07/23/2021
Unsupervised Domain Adaptation for Video Semantic Segmentation
Unsupervised Domain Adaptation for semantic segmentation has gained imme...
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12/09/2020
Two-phase Pseudo Label Densification for Self-training based Domain Adaptation
Recently, deep self-training approaches emerged as a powerful solution t...
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04/16/2020
Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision
Convolutional neural network-based approaches have achieved remarkable p...
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12/24/2018
