https://github.com/jbr97/urm
공식 코드Single Domain Generalization for Few-Shot Counting via Universal Representation Matching
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Single Domain Generalization for Few-Shot Counting via Universal Representation Matching
Deep Multimodal Fusion for Generalizable Person Re-identification
Information Subtraction: Learning Representations for Conditional Entropy
Pixel-in-Pixel Net: Towards Efficient Facial Landmark Detection in the Wild
Improving Vision Transformers by Revisiting High-frequency Components
CLIP-Powered Domain Generalization and Domain Adaptation: A Comprehensive Survey
Generalizing to Unseen Domains: A Survey on Domain Generalization
CLAP-S: Support Set Based Adaptation for Downstream Fiber-optic Acoustic Recognition
DomCLP: Domain-wise Contrastive Learning with Prototype Mixup for Unsupervised Domain Generalization
Domain Generalization through the Lens of Angular Invariance
Algorithmic Fairness Generalization under Covariate and Dependence Shifts Simultaneously
Deep Learning for Hate Speech Detection: A Comparative Study
Explaining Domain Shifts in Language: Concept erasing for Interpretable Image Classification
Feature Stylization and Domain-aware Contrastive Learning for Domain Generalization
POEM: Polarization of Embeddings for Domain-Invariant Representations
PARDON: Privacy-Aware and Robust Federated Domain Generalization
Domain generalization of 3D semantic segmentation in autonomous driving
Collaborative Semantic Aggregation and Calibration for Federated Domain Generalization
Domain-Specific Bias Filtering for Single Labeled Domain Generalization
FSDR: Frequency Space Domain Randomization for Domain Generalization
Rethinking Data Augmentation for Single-source Domain Generalization in Medical Image Segmentation
Domain Generalization by Mutual-Information Regularization with Pre-trained Models
MatchSeg: Towards Better Segmentation via Reference Image Matching
Do Vision Foundation Models Enhance Domain Generalization in Medical Image Segmentation?
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.