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 1376–1400 of 1751 papers

Title	Date	Tasks	Status	Hype
Discovery of New Multi-Level Features for Domain Generalization via Knowledge Corruption	Sep 9, 2021	Domain Generalization	—Unverified	0
Class-conditioned Domain Generalization via Wasserstein Distributional Robust Optimization	Sep 8, 2021	Domain Generalization	—Unverified	0
Fishr: Invariant Gradient Variances for Out-of-Distribution Generalization	Sep 7, 2021	Domain GeneralizationOut-of-Distribution Generalization	CodeCode Available	1
Improved RAMEN: Towards Domain Generalization for Visual Question Answering	Sep 6, 2021	Domain GeneralizationQuestion Answering	CodeCode Available	0
NAS-OoD: Neural Architecture Search for Out-of-Distribution Generalization	Sep 5, 2021	Domain GeneralizationNeural Architecture Search	CodeCode Available	1
Barycentric-alignment and reconstruction loss minimization for domain generalization	Sep 4, 2021	Domain GeneralizationRepresentation Learning	CodeCode Available	0
Multi-View Spatial-Temporal Graph Convolutional Networks with Domain Generalization for Sleep Stage Classification	Sep 4, 2021	ClassificationDomain Generalization	CodeCode Available	1
MitoDet: Simple and robust mitosis detection	Sep 2, 2021	Data AugmentationDomain Generalization	—Unverified	0
Multi-source Domain Adaptation Using Gradient Reversal Layer for Mitotic Cell Detection	Sep 2, 2021	Cell DetectionDomain Adaptation	—Unverified	0
Domain-Robust Mitotic Figure Detection with Style Transfer	Sep 2, 2021	Domain GeneralizationStyle Transfer	—Unverified	0
Learning to Prompt for Vision-Language Models	Sep 2, 2021	Domain GeneralizationFew-shot Age Estimation	CodeCode Available	2
Stain-Robust Mitotic Figure Detection for the Mitosis Domain Generalization Challenge	Sep 2, 2021	Domain Generalization	—Unverified	0
Rotation Invariance and Extensive Data Augmentation: a strategy for the Mitosis Domain Generalization (MIDOG) Challenge	Sep 2, 2021	Data AugmentationDomain Generalization	—Unverified	0
Towards Domain-Generalizable Paraphrase Identification by Avoiding the Shortcut Learning	Sep 1, 2021	Domain GeneralizationParaphrase Identification	—Unverified	0
Towards Improving Adversarial Training of NLP Models	Sep 1, 2021	Domain GeneralizationSentence	CodeCode Available	1
Domain Adaptive Cascade R-CNN for MItosis DOmain Generalization (MIDOG) Challenge	Sep 1, 2021	Data AugmentationDomain Generalization	—Unverified	0
Self-balanced Learning For Domain Generalization	Aug 31, 2021	Domain Generalization	—Unverified	0
AP-10K: A Benchmark for Animal Pose Estimation in the Wild	Aug 28, 2021	Animal Pose EstimationDiversity	CodeCode Available	1
Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing	Aug 27, 2021	BenchmarkingData Augmentation	CodeCode Available	1
Learning to Diversify for Single Domain Generalization	Aug 26, 2021	Domain GeneralizationPhoto to Rest Generalization	CodeCode Available	1
Generalize then Adapt: Source-Free Domain Adaptive Semantic Segmentation	Aug 25, 2021	Domain AdaptationDomain Generalization	CodeCode Available	1
Domain Adversarial RetinaNet as a Reference Algorithm for the MItosis DOmain Generalization Challenge	Aug 25, 2021	Domain Generalization	—Unverified	0
Discovering Spatial Relationships by Transformers for Domain Generalization	Aug 23, 2021	Domain Generalization	—Unverified	0
Discriminative Domain-Invariant Adversarial Network for Deep Domain Generalization	Aug 20, 2021	Domain Generalization	—Unverified	0
Exploring Data Aggregation and Transformations to Generalize across Visual Domains	Aug 20, 2021	Data AugmentationDomain Adaptation	CodeCode Available	1

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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