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Domain Generalization
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The idea of Domain Generalization is to learn from one or multiple training domains, to extract a domain-agnostic model which can be applied to an unseen domain
Source: Diagram Image Retrieval using Sketch-Based Deep Learning and Transfer Learning
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
LG-Gaze: Learning Geometry-aware Continuous Prompts for Language-Guided Gaze Estimation
DRIFTS: Optimizing Domain Randomization with Synthetic Data and Weight Interpolation for Fetal Brain Tissue Segmentation
Feature-Space Semantic Invariance: Enhanced OOD Detection for Open-Set Domain Generalization
Prompt-Guided Internal States for Hallucination Detection of Large Language Models
In the Era of Prompt Learning with Vision-Language Models
Generalizable Single-Source Cross-modality Medical Image Segmentation via Invariant Causal Mechanisms
Domain Generalization for Cross-Receiver Radio Frequency Fingerprint Identification
Beyond Model Adaptation at Test Time: A Survey
Generalize or Detect? Towards Robust Semantic Segmentation Under Multiple Distribution Shifts
WiFlexFormer: Efficient WiFi-Based Person-Centric Sensing
Domain Expansion and Boundary Growth for Open-Set Single-Source Domain Generalization
Navigating Distribution Shifts in Medical Image Analysis: A Survey
Improving Domain Generalization in Self-supervised Monocular Depth Estimation via Stabilized Adversarial Training
Divergent Domains, Convergent Grading: Enhancing Generalization in Diabetic Retinopathy Grading
FEED: Fairness-Enhanced Meta-Learning for Domain Generalization
MADOD: Generalizing OOD Detection to Unseen Domains via G-Invariance Meta-Learning
Is Multiple Object Tracking a Matter of Specialization?
Recovering Complete Actions for Cross-dataset Skeleton Action Recognition
PARDON: Privacy-Aware and Robust Federated Domain Generalization
CrossEarth: Geospatial Vision Foundation Model for Domain Generalizable Remote Sensing Semantic Segmentation
Unified Domain Generalization and Adaptation for Multi-View 3D Object Detection
Point-PRC: A Prompt Learning Based Regulation Framework for Generalizable Point Cloud Analysis
PaPaGei: Open Foundation Models for Optical Physiological Signals
Beyond Interpretability: The Gains of Feature Monosemanticity on Model Robustness
RARe: Retrieval Augmented Retrieval with In-Context Examples
Anatomical 3D Style Transfer Enabling Efficient Federated Learning with Extremely Low Communication Costs
Prompt Diffusion Robustifies Any-Modality Prompt Learning
LFME: A Simple Framework for Learning from Multiple Experts in Domain Generalization
DomainSum: A Hierarchical Benchmark for Fine-Grained Domain Shift in Abstractive Text Summarization
How Important are Data Augmentations to Close the Domain Gap for Object Detection in Orbit?
START: A Generalized State Space Model with Saliency-Driven Token-Aware Transformation
Towards Combating Frequency Simplicity-biased Learning for Domain Generalization
Fine-Tuning Pre-trained Language Models for Robust Causal Representation Learning
Tackling domain generalization for out-of-distribution endoscopic imaging
Syn2Real Domain Generalization for Underwater Mine-like Object Detection Using Side-Scan Sonar
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