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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.
NeuGen: Amplifying the 'Neural' in Neural Radiance Fields for Domain Generalization
Depth-Sensitive Soft Suppression with RGB-D Inter-Modal Stylization Flow for Domain Generalization Semantic Segmentation
TAROT: Towards Essentially Domain-Invariant Robustness with Theoretical Justification
Leveraging Vision-Language Models for Visual Grounding and Analysis of Automotive UI
Domain-Adversarial Anatomical Graph Networks for Cross-User Human Activity Recognition
Panoramic Out-of-Distribution Segmentation
FedSDAF: Leveraging Source Domain Awareness for Enhanced Federated Domain Generalization
GRAIL: Graph Edit Distance and Node Alignment Using LLM-Generated Code
Robust AI-Generated Face Detection with Imbalanced Data
A Sensor Agnostic Domain Generalization Framework for Leveraging Geospatial Foundation Models: Enhancing Semantic Segmentation viaSynergistic Pseudo-Labeling and Generative Learning
Adapting In-Domain Few-Shot Segmentation to New Domains without Retraining
Effective Inference-Free Retrieval for Learned Sparse Representations
Reinforcement Learning for Reasoning in Large Language Models with One Training Example
Low-Rank Adaptive Structural Priors for Generalizable Diabetic Retinopathy Grading
Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation
FrogDogNet: Fourier frequency Retained visual prompt Output Guidance for Domain Generalization of CLIP in Remote Sensing
Unsupervised Time-Series Signal Analysis with Autoencoders and Vision Transformers: A Review of Architectures and Applications
iMedic: Towards Smartphone-based Self-Auscultation Tool for AI-Powered Pediatric Respiratory Assessment
DONOD: Robust and Generalizable Instruction Fine-Tuning for LLMs via Model-Intrinsic Dataset Pruning
CLIP-Powered Domain Generalization and Domain Adaptation: A Comprehensive Survey
Vision and Language Integration for Domain Generalization
DG-MVP: 3D Domain Generalization via Multiple Views of Point Clouds for Classification
When is Task Vector Provably Effective for Model Editing? A Generalization Analysis of Nonlinear Transformers
Mixture-of-Shape-Experts (MoSE): End-to-End Shape Dictionary Framework to Prompt SAM for Generalizable Medical Segmentation
RT-DATR:Real-time Unsupervised Domain Adaptive Detection Transformer with Adversarial Feature Learning
DGFamba: Learning Flow Factorized State Space for Visual Domain Generalization
Learning Fine-grained Domain Generalization via Hyperbolic State Space Hallucination
Domain Generalization through Attenuation of Domain-Specific Information
Earth-Adapter: Bridge the Geospatial Domain Gaps with Mixture of Frequency Adaptation
Decentralized Federated Domain Generalization with Style Sharing: A Formal Modeling and Convergence Analysis
Enhance Then Search: An Augmentation-Search Strategy with Foundation Models for Cross-Domain Few-Shot Object Detection
Mamba as a Bridge: Where Vision Foundation Models Meet Vision Language Models for Domain-Generalized Semantic Segmentation
Optimizing Specific and Shared Parameters for Efficient Parameter Tuning
Generative Classifier for Domain Generalization
Adapting Large Language Models for Multi-Domain Retrieval-Augmented-Generation
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