Domain Generalization
641 papers with code • 18 benchmarks • 24 datasets
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
Benchmarks
These leaderboards are used to track progress in Domain Generalization
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
Libraries
Use these libraries to find Domain Generalization models and implementationsDatasets
Fashion-MNIST
Office-Home
DomainNet
PACS
ImageNet-C
ImageNet-R
ImageNet-A
ImageNet-Sketch
Stylized ImageNet
WildDash
Latest papers
ConDiSR: Contrastive Disentanglement and Style Regularization for Single Domain Generalization
We evaluate our method on the complex task of multicenter histopathology image classification, comparing it against state-of-the-art (SOTA) SDG baselines.
Unleashing the Power of Meta-tuning for Few-shot Generalization Through Sparse Interpolated Experts
szc12153/sparse_meta_tuning
•
•
Conventional wisdom suggests parameter-efficient fine-tuning of foundation models as the state-of-the-art method for transfer learning in vision, replacing the rich literature of alternatives such as meta-learning.
A Causal Inspired Early-Branching Structure for Domain Generalization
By d-separation, we observe that the causal feature can be further characterized by being independent of the domain conditioned on the object, and we propose the following two strategies as complements for the basic framework.
Robust Synthetic-to-Real Transfer for Stereo Matching
With advancements in domain generalized stereo matching networks, models pre-trained on synthetic data demonstrate strong robustness to unseen domains.
Advancing Generalizable Remote Physiological Measurement through the Integration of Explicit and Implicit Prior Knowledge
keke-nice/greip
•
•
Remote photoplethysmography (rPPG) is a promising technology that captures physiological signals from face videos, with potential applications in medical health, emotional computing, and biosecurity recognition.
A Study on Domain Generalization for Failure Detection through Human Reactions in HRI
This makes domain generalization - retaining performance in different settings - a critical issue.
X-Shot: A Unified System to Handle Frequent, Few-shot and Zero-shot Learning Simultaneously in Classification
xhz0809/x-shot
•
•
In recent years, few-shot and zero-shot learning, which learn to predict labels with limited annotated instances, have garnered significant attention.
Suppress and Rebalance: Towards Generalized Multi-Modal Face Anti-Spoofing
Face Anti-Spoofing (FAS) is crucial for securing face recognition systems against presentation attacks.
Gradient Alignment for Cross-Domain Face Anti-Spoofing
Recent advancements in domain generalization (DG) for face anti-spoofing (FAS) have garnered considerable attention.
Rethinking Multi-domain Generalization with A General Learning Objective
Multi-domain generalization (mDG) is universally aimed to minimize the discrepancy between training and testing distributions to enhance marginal-to-label distribution mapping.
