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 501525 of 1751 papers

TitleStatusHype
Domain Generalization Strategy to Train Classifiers Robust to Spatial-Temporal ShiftCode1
Domain Generalization for Medical Imaging Classification with Linear-Dependency RegularizationCode1
Learning Robust Global Representations by Penalizing Local Predictive PowerCode1
Domain Generalization using Causal MatchingCode1
Domain Generalization for Prostate Segmentation in Transrectal Ultrasound Images: A Multi-center StudyCode1
Masked Autoencoders Are Scalable Vision LearnersCode1
An Information-theoretic Approach to Distribution ShiftsCode1
Matching-space Stereo Networks for Cross-domain GeneralizationCode1
Domain Generalization for Vision-based Driving Trajectory GenerationCode1
MatchSeg: Towards Better Segmentation via Reference Image MatchingCode1
M-HOF-Opt: Multi-Objective Hierarchical Output Feedback Optimization via Multiplier Induced Loss Landscape SchedulingCode1
Multi-View Spatial-Temporal Graph Convolutional Networks with Domain Generalization for Sleep Stage ClassificationCode1
NICO++: Towards Better Benchmarking for Domain GeneralizationCode1
Progressive Domain Expansion Network for Single Domain GeneralizationCode1
Domain Generalization Using Large Pretrained Models with Mixture-of-AdaptersCode1
Domain Generalization via Entropy RegularizationCode1
MIMII DG: Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection for Domain Generalization TaskCode1
MI-SegNet: Mutual Information-Based US Segmentation for Unseen Domain GeneralizationCode1
Domain Generalization via Rationale InvarianceCode1
Domain-Generalized Face Anti-Spoofing with Unknown AttacksCode1
Domain Generalization for Text Classification with Memory-Based Supervised Contrastive LearningCode0
Medical Image Segmentation via Single-Source Domain Generalization with Random Amplitude Spectrum SynthesisCode0
Certifying Out-of-Domain Generalization for Blackbox FunctionsCode0
A New Dataset Based on Images Taken by Blind People for Testing the Robustness of Image Classification Models Trained for ImageNet CategoriesCode0
Magnification Generalization for Histopathology Image EmbeddingCode0
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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