SOTAVerified|Agents Browse Leaderboard About

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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1411–1420 of 1751 papers

Title	Date	Tasks	Status	Hype
Domain Generalization under Conditional and Label Shifts via Variational Bayesian Inference	Jul 22, 2021	Bayesian InferenceDomain Generalization	—Unverified	0
Joint Semi-supervised 3D Super-Resolution and Segmentation with Mixed Adversarial Gaussian Domain Adaptation	Jul 16, 2021	Domain AdaptationDomain Generalization	—Unverified	0
Context-Conditional Adaptation for Recognizing Unseen Classes in Unseen Domains	Jul 15, 2021	Domain GeneralizationZero-Shot Learning	—Unverified	0
Domain Generalization with Pseudo-Domain Label for Face Anti-Spoofing	Jul 14, 2021	Domain GeneralizationFace Anti-Spoofing	—Unverified	0
Towards Unsupervised Domain Generalization	Jul 13, 2021	Domain GeneralizationRepresentation Learning	—Unverified	0
Exploiting Image Translations via Ensemble Self-Supervised Learning for Unsupervised Domain Adaptation	Jul 13, 2021	Domain AdaptationDomain Generalization	—Unverified	0
Structured Latent Embeddings for Recognizing Unseen Classes in Unseen Domains	Jul 12, 2021	Domain GeneralizationZero-Shot Learning	—Unverified	0
Anatomy of Domain Shift Impact on U-Net Layers in MRI Segmentation	Jul 10, 2021	AnatomyDomain Adaptation	CodeCode Available	1
On the Challenges of Open World Recognitionunder Shifting Visual Domains	Jul 9, 2021	Domain GeneralizationObject Recognition	CodeCode Available	1
Understanding the Limits of Unsupervised Domain Adaptation via Data Poisoning	Jul 8, 2021	Data PoisoningDomain Adaptation	CodeCode Available	0

Show:10 25 50

← PrevPage 142 of 176Next →

All datasets PACS VizWiz-Classification ImageNet-C Office-Home ImageNet-A ImageNet-R DomainNet VLCS TerraIncognita GTA-to-Avg(Cityscapes,BDD,Mapillary)ImageNet-Sketch GTA5 to Cityscapes

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	SIMPLE+	Average Accuracy	99	—	Unverified
2	PromptStyler (CLIP, ViT-L/14)	Average Accuracy	98.6	—	Unverified
3	GMDG (RegNetY-16GF, SWAD)	Average Accuracy	97.9	—	Unverified
4	D-Triplet(RegNetY-16GF)	Average Accuracy	97.6	—	Unverified
5	MoA (OpenCLIP, ViT-B/16)	Average Accuracy	97.4	—	Unverified
6	GMDG (e RegNetY-16GF)	Average Accuracy	97.3	—	Unverified
7	PromptStyler (CLIP, ViT-B/16)	Average Accuracy	97.2	—	Unverified
8	SPG (CLIP, ViT-B/16)	Average Accuracy	97	—	Unverified
9	CAR-FT (CLIP, ViT-B/16)	Average Accuracy	96.8	—	Unverified
10	MIRO (RegNetY-16GF, SWAD)	Average Accuracy	96.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ViT-8/B-224	Accuracy - Clean Images	450	—	Unverified
2	VOLO-D5	Accuracy - All Images	57.2	—	Unverified
3	ConvNeXt-B	Accuracy - All Images	53.5	—	Unverified
4	ResNeXt-101 32x16d	Accuracy - All Images	51.7	—	Unverified
5	EfficientNet-B8 (advprop+autoaug)	Accuracy - All Images	50.5	—	Unverified
6	EfficientNet-B7 (advprop+autoaug)	Accuracy - All Images	49.7	—	Unverified
7	EfficientNet-B6 (advprop+autoaug)	Accuracy - All Images	49.6	—	Unverified
8	EfficientNet-B5 (advprop+autoaug)	Accuracy - All Images	49.1	—	Unverified
9	ViT-16/L-224	Accuracy - All Images	49	—	Unverified
10	ResNet-50 (gn)	Accuracy - All Images	48.9	—	Unverified