SOTAVerified

Domain Generalization

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

Papers

Showing 14261450 of 1751 papers

TitleStatusHype
Which Invariance Should We Transfer? A Causal Minimax Learning ApproachCode1
PoliTO-IIT Submission to the EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition0
Global Filter Networks for Image ClassificationCode1
Zero-Shot Estimation of Base Models' Weights in Ensemble of Machine Reading Comprehension Systems for Robust Generalization0
Dual Reweighting Domain Generalization for Face Presentation Attack Detection0
Domain-Class Correlation Decomposition for Generalizable Person Re-Identification0
Critically examining the Domain Generalizability of Facial Expression Recognition models0
Deep Learning for Face Anti-Spoofing: A SurveyCode1
VOLO: Vision Outlooker for Visual RecognitionCode1
Generalization on Unseen Domains via Inference-Time Label-Preserving Target Projections0
Adversarial Invariant LearningCode0
Person30K: A Dual-Meta Generalization Network for Person Re-Identification0
Quality-Agnostic Image Recognition via Invertible DecoderCode0
Iterative Feature Matching: Toward Provable Domain Generalization with Logarithmic Environments0
On Invariance Penalties for Risk Minimization0
X-FACT: A New Benchmark Dataset for Multilingual Fact CheckingCode1
AtrialGeneral: Domain Generalization for Left Atrial Segmentation of Multi-Center LGE MRIs0
Behavioral Priors and Dynamics Models: Improving Performance and Domain Transfer in Offline RL0
Encouraging Intra-Class Diversity Through a Reverse Contrastive Loss for Better Single-Source Domain Generalization0
Domain Generalization on Medical Imaging Classification using Episodic Training with Task Augmentation0
Harmonization with Flow-based Causal InferenceCode0
Invariant Information Bottleneck for Domain Generalization0
Parameter-efficient Multi-task Fine-tuning for Transformers via Shared HypernetworksCode1
Towards a Theoretical Framework of Out-of-Distribution Generalization0
Adversarial Semantic Hallucination for Domain Generalized Semantic SegmentationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SIMPLE+Average Accuracy99Unverified
2PromptStyler (CLIP, ViT-L/14)Average Accuracy98.6Unverified
3GMDG (RegNetY-16GF, SWAD)Average Accuracy97.9Unverified
4D-Triplet(RegNetY-16GF)Average Accuracy97.6Unverified
5MoA (OpenCLIP, ViT-B/16)Average Accuracy97.4Unverified
6GMDG (e RegNetY-16GF)Average Accuracy97.3Unverified
7PromptStyler (CLIP, ViT-B/16)Average Accuracy97.2Unverified
8SPG (CLIP, ViT-B/16)Average Accuracy97Unverified
9CAR-FT (CLIP, ViT-B/16)Average Accuracy96.8Unverified
10MIRO (RegNetY-16GF, SWAD)Average Accuracy96.8Unverified
#ModelMetricClaimedVerifiedStatus
1ViT-8/B-224Accuracy - Clean Images450Unverified
2VOLO-D5Accuracy - All Images57.2Unverified
3ConvNeXt-BAccuracy - All Images53.5Unverified
4ResNeXt-101 32x16dAccuracy - All Images51.7Unverified
5EfficientNet-B8 (advprop+autoaug)Accuracy - All Images50.5Unverified
6EfficientNet-B7 (advprop+autoaug)Accuracy - All Images49.7Unverified
7EfficientNet-B6 (advprop+autoaug)Accuracy - All Images49.6Unverified
8EfficientNet-B5 (advprop+autoaug)Accuracy - All Images49.1Unverified
9ViT-16/L-224Accuracy - All Images49Unverified
10ResNet-50 (gn)Accuracy - All Images48.9Unverified