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 71–80 of 1751 papers

Title	Date	Tasks	Status	Hype
Understanding The Robustness in Vision Transformers	Apr 26, 2022	Domain GeneralizationImage Classification	CodeCode Available	2
Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time	Mar 10, 2022	Domain Generalization	CodeCode Available	2
BatchFormer: Learning to Explore Sample Relationships for Robust Representation Learning	Mar 3, 2022	Compositional Zero-Shot LearningContrastive Learning	CodeCode Available	2
Pedestrian Detection: Domain Generalization, CNNs, Transformers and Beyond	Jan 10, 2022	AttributeAutonomous Driving	CodeCode Available	2
Learning to Prompt for Vision-Language Models	Sep 2, 2021	Domain GeneralizationFew-shot Age Estimation	CodeCode Available	2
Building Computationally Efficient and Well-Generalizing Person Re-Identification Models with Metric Learning	Mar 17, 2020	Domain GeneralizationFace Recognition	CodeCode Available	2
On the limits of cross-domain generalization in automated X-ray prediction	Feb 6, 2020	DiagnosticDomain Generalization	CodeCode Available	2
RandAugment: Practical automated data augmentation with a reduced search space	Sep 30, 2019	Data AugmentationDomain Generalization	CodeCode Available	2
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations	Mar 28, 2019	Adversarial DefenseBenchmarking	CodeCode Available	2
InstructFLIP: Exploring Unified Vision-Language Model for Face Anti-spoofing	Jul 16, 2025	Domain GeneralizationFace Anti-Spoofing	CodeCode Available	1

Show:10 25 50

← PrevPage 8 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