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 12761300 of 1751 papers

TitleStatusHype
Contrastive Regression for Domain Adaptation on Gaze Estimation0
The Two Dimensions of Worst-Case Training and Their Integrated Effect for Out-of-Domain Generalization0
PCL: Proxy-Based Contrastive Learning for Domain GeneralizationCode1
Meta Distribution Alignment for Generalizable Person Re-IdentificationCode0
BoosterNet: Improving Domain Generalization of Deep Neural Nets Using Culpability-Ranked Features0
Style Neophile: Constantly Seeking Novel Styles for Domain Generalization0
Meta Convolutional Neural Networks for Single Domain Generalization0
Optimal Representations for Covariate ShiftCode1
Feature Generation and Hypothesis Verification for Reliable Face Anti-SpoofingCode0
PRIME: A few primitives can boost robustness to common corruptionsCode1
Meta-Learned Feature Critics for Domain Generalized Semantic Segmentation0
MVDG: A Unified Multi-view Framework for Domain GeneralizationCode0
Recur, Attend or Convolve? On Whether Temporal Modeling Matters for Cross-Domain Robustness in Action RecognitionCode0
Generalizable Cross-modality Medical Image Segmentation via Style Augmentation and Dual NormalizationCode1
Automated Domain Discovery from Multiple Sources to Improve Zero-Shot GeneralizationCode0
Large Dual Encoders Are Generalizable RetrieversCode1
Cross-Domain Generalization and Knowledge Transfer in Transformers Trained on Legal Data0
A Style and Semantic Memory Mechanism for Domain Generalization0
Adaptive Methods for Aggregated Domain GeneralizationCode1
Rethinking the Authorship Verification Experimental SetupsCode0
3D-VField: Adversarial Augmentation of Point Clouds for Domain Generalization in 3D Object Detection0
PLACE dropout: A Progressive Layer-wise and Channel-wise Dropout for Domain GeneralizationCode0
Unsupervised Domain Adaptation for Semantic Image Segmentation: a Comprehensive Survey0
Unsupervised Domain Generalization by Learning a Bridge Across DomainsCode1
Causal-based Time Series Domain Generalization for Vehicle Intention Prediction0
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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