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Test-time Adaptation

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Showing 351–400 of 484 papers

TitleStatusHype
Test-time adaptation for image compression with distribution regularization—0
Test-Time Adaptation for Nighttime Color-Thermal Semantic Segmentation—0
Test-Time Adaptation for Out-of-distributed Image Inpainting—0
Test-Time Adaptation for Point Cloud Upsampling Using Meta-Learning—0
Test-time Adaptation for Real Image Denoising via Meta-transfer Learning—0
Test-Time Adaptation for Super-Resolution: You Only Need to Overfit on a Few More Images—0
Test-Time Adaptation for Visual Document Understanding—0
Test-time Adaptation Meets Image Enhancement: Improving Accuracy via Uncertainty-aware Logit Switching—0
Test-Time Adaptation of 3D Point Clouds via Denoising Diffusion Models—0
Test-Time Adaptation to Distribution Shift by Confidence Maximization and Input Transformation—0
Test-Time Adaptation to Distribution Shifts by Confidence Maximization and Input Transformation—0
Test-Time Adaptation Toward Personalized Speech Enhancement: Zero-Shot Learning with Knowledge Distillation—0
Test-time Adaptation vs. Training-time Generalization: A Case Study in Human Instance Segmentation using Keypoints Estimation—0
Test-Time Adaptation with Perturbation Consistency Learning—0
Test-Time Adaptation with Principal Component Analysis—0
Test Time Adaptation With Regularized Loss for Weakly Supervised Salient Object Detection—0
Temporal Test-Time Adaptation with State-Space Models—0
Test-time Batch Statistics Calibration for Covariate Shift—0
Test-Time Certifiable Self-Supervision to Bridge the Sim2Real Gap in Event-Based Satellite Pose Estimation—0
Test-Time Fast Adaptation for Dynamic Scene Deblurring via Meta-Auxiliary Learning—0
Test-Time Intensity Consistency Adaptation for Shadow Detection—0
Test-time Loss Landscape Adaptation for Zero-Shot Generalization in Vision-Language Models—0
Test Time Robustification of Deep Models via Adaptation and Augmentation—0
Test-Time Training on Graphs with Large Language Models (LLMs)—0
Towards Clinician-Preferred Segmentation: Leveraging Human-in-the-Loop for Test Time Adaptation in Medical Image Segmentation—0
A Novel Training Framework for Physics-informed Neural Networks: Towards Real-time Applications in Ultrafast Ultrasound Blood Flow Imaging—0
Towards Understanding GD with Hard and Conjugate Pseudo-labels for Test-Time Adaptation—0
Track2Act: Predicting Point Tracks from Internet Videos enables Generalizable Robot Manipulation—0
TRAIL: Transferable Robust Adversarial Images via Latent diffusion—0
Train/Test-Time Adaptation with Retrieval—0
TransAdapt: A Transformative Framework for Online Test Time Adaptive Semantic Segmentation—0
TTA-COPE: Test-Time Adaptation for Category-Level Object Pose Estimation—0
TTAQ: Towards Stable Post-training Quantization in Continuous Domain Adaptation—0
TTN: A Domain-Shift Aware Batch Normalization in Test-Time Adaptation—0
TTVD: Towards a Geometric Framework for Test-Time Adaptation Based on Voronoi Diagram—0
Turn Down the Noise: Leveraging Diffusion Models for Test-time Adaptation via Pseudo-label Ensembling—0
Uncertainty-Aware Test-Time Adaptation for Inverse Consistent Diffeomorphic Lung Image Registration—0
Uncertainty-Calibrated Test-Time Model Adaptation without Forgetting—0
Uncovering Adversarial Risks of Test-Time Adaptation—0
Universal Test-time Adaptation through Weight Ensembling, Diversity Weighting, and Prior Correction—0
Unseen Object Instance Segmentation with Fully Test-time RGB-D Embeddings Adaptation—0
Unsupervised Adaptation of Semantic Segmentation Models without Source Data—0
Unsupervised Domain Adaptation for Semantic Image Segmentation: a Comprehensive Survey—0
Plug-and-Play Transformer Modules for Test-Time Adaptation—0
UrbanMind: Urban Dynamics Prediction with Multifaceted Spatial-Temporal Large Language Models—0
Variational Continual Test-Time Adaptation—0
Visual Prompt Tuning for Test-time Domain Adaptation—0
VPA: Fully Test-Time Visual Prompt Adaptation—0
Whoever Started the Interference Should End It: Guiding Data-Free Model Merging via Task Vectors—0
Self-Adaptively Learning to Demoiré from Focused and Defocused Image Pairs—0
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