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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.
Context-Aware Self-Adaptation for Domain Generalization
A Practical Synthesis of Detecting AI-Generated Textual, Visual, and Audio Content
Context-Aware Human Behavior Prediction Using Multimodal Large Language Models: Challenges and Insights
Are Domain Generalization Benchmarks with Accuracy on the Line Misspecified?
DGSAM: Domain Generalization via Individual Sharpness-Aware Minimization
Partial Transportability for Domain Generalization
Enhancing Learnable Descriptive Convolutional Vision Transformer for Face Anti-Spoofing
Unsupervised Anomaly Detection in Multivariate Time Series across Heterogeneous Domains
Concept-Aware LoRA for Domain-Aligned Segmentation Dataset Generation
A Dataset for Semantic Segmentation in the Presence of Unknowns
Generating Synthetic Oracle Datasets to Analyze Noise Impact: A Study on Building Function Classification Using Tweets
Zero-shot Domain Generalization of Foundational Models for 3D Medical Image Segmentation: An Experimental Study
ReCoM: Realistic Co-Speech Motion Generation with Recurrent Embedded Transformer
Feature Modulation for Semi-Supervised Domain Generalization without Domain Labels
A Causal Perspective of Stock Prediction Models
Explaining Domain Shifts in Language: Concept erasing for Interpretable Image Classification
Advancing Cross-Organ Domain Generalization with Test-Time Style Transfer and Diversity Enhancement
OCRT: Boosting Foundation Models in the Open World with Object-Concept-Relation Triad
Balanced Direction from Multifarious Choices: Arithmetic Meta-Learning for Domain Generalization
DGAR: A Unified Domain Generalization Framework for RF-Enabled Human Activity Recognition
A Language Anchor-Guided Method for Robust Noisy Domain Generalization
No Thing, Nothing: Highlighting Safety-Critical Classes for Robust LiDAR Semantic Segmentation in Adverse Weather
OSLoPrompt: Bridging Low-Supervision Challenges and Open-Set Domain Generalization in CLIP
Rethinking Robustness in Machine Learning: A Posterior Agreement Approach
V2X-DG: Domain Generalization for Vehicle-to-Everything Cooperative Perception
Unlocking the Potential of Unlabeled Data in Semi-Supervised Domain Generalization
SCORE: Soft Label Compression-Centric Dataset Condensation via Coding Rate Optimization
COPA: Comparing the Incomparable to Explore the Pareto Front
Robust Object Detection of Underwater Robot based on Domain Generalization
DeepPerception: Advancing R1-like Cognitive Visual Perception in MLLMs for Knowledge-Intensive Visual Grounding
Test-Time Domain Generalization via Universe Learning: A Multi-Graph Matching Approach for Medical Image Segmentation
Let Synthetic Data Shine: Domain Reassembly and Soft-Fusion for Single Domain Generalization
TLAC: Two-stage LMM Augmented CLIP for Zero-Shot Classification
ReBot: Scaling Robot Learning with Real-to-Sim-to-Real Robotic Video Synthesis
UBMF: Uncertainty-Aware Bayesian Meta-Learning Framework for Fault Diagnosis with Imbalanced Industrial Data
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