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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 726–750 of 1751 papers

TitleStatusHype
DIR: Retrieval-Augmented Image Captioning with Comprehensive Understanding—0
A Cross-Scene Benchmark for Open-World Drone Active Tracking—0
Actions and Objects Pathways for Domain Adaptation in Video Question Answering—0
QUOTA: Quantifying Objects with Text-to-Image Models for Any Domain—0
On the Generalization of Handwritten Text Recognition Models—0
Style-Pro: Style-Guided Prompt Learning for Generalizable Vision-Language Models—0
TIDE: Training Locally Interpretable Domain Generalization Models Enables Test-time Correction—0
Boundless Across Domains: A New Paradigm of Adaptive Feature and Cross-Attention for Domain Generalization in Medical Image Segmentation—0
MLDGG: Meta-Learning for Domain Generalization on Graphs—0
Fair Distillation: Teaching Fairness from Biased Teachers in Medical Imaging—0
Federated Domain Generalization via Prompt Learning and AggregationCode0
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation—0
Real-time Adapting Routing (RAR): Improving Efficiency Through Continuous Learning in Software Powered by Layered Foundation Models—0
LG-Gaze: Learning Geometry-aware Continuous Prompts for Language-Guided Gaze Estimation—0
Feature-Space Semantic Invariance: Enhanced OOD Detection for Open-Set Domain Generalization—0
DRIFTS: Optimizing Domain Randomization with Synthetic Data and Weight Interpolation for Fetal Brain Tissue Segmentation—0
Generalizable Single-Source Cross-modality Medical Image Segmentation via Invariant Causal MechanismsCode0
In the Era of Prompt Learning with Vision-Language Models—0
Prompt-Guided Internal States for Hallucination Detection of Large Language Models—0
Domain Generalization for Cross-Receiver Radio Frequency Fingerprint Identification—0
WiFlexFormer: Efficient WiFi-Based Person-Centric SensingCode0
Navigating Distribution Shifts in Medical Image Analysis: A Survey—0
Domain Expansion and Boundary Growth for Open-Set Single-Source Domain Generalization—0
Divergent Domains, Convergent Grading: Enhancing Generalization in Diabetic Retinopathy GradingCode0
Improving Domain Generalization in Self-supervised Monocular Depth Estimation via Stabilized Adversarial Training—0
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All datasetsPACSVizWiz-ClassificationImageNet-COffice-HomeImageNet-AImageNet-RDomainNetVLCSTerraIncognitaGTA-to-Avg(Cityscapes,BDD,Mapillary)ImageNet-SketchGTA5 to Cityscapes

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SIMPLE+Average Accuracy99—Unverified
2PromptStyler (CLIP, ViT-L/14)Average Accuracy98.6—Unverified
3GMDG (RegNetY-16GF, SWAD)Average Accuracy97.9—Unverified
4D-Triplet(RegNetY-16GF)Average Accuracy97.6—Unverified
5MoA (OpenCLIP, ViT-B/16)Average Accuracy97.4—Unverified
6GMDG (e RegNetY-16GF)Average Accuracy97.3—Unverified
7PromptStyler (CLIP, ViT-B/16)Average Accuracy97.2—Unverified
8SPG (CLIP, ViT-B/16)Average Accuracy97—Unverified
9CAR-FT (CLIP, ViT-B/16)Average Accuracy96.8—Unverified
10MIRO (RegNetY-16GF, SWAD)Average Accuracy96.8—Unverified
#ModelMetricClaimedVerifiedStatus
1ViT-8/B-224Accuracy - Clean Images450—Unverified
2VOLO-D5Accuracy - All Images57.2—Unverified
3ConvNeXt-BAccuracy - All Images53.5—Unverified
4ResNeXt-101 32x16dAccuracy - All Images51.7—Unverified
5EfficientNet-B8 (advprop+autoaug)Accuracy - All Images50.5—Unverified
6EfficientNet-B7 (advprop+autoaug)Accuracy - All Images49.7—Unverified
7EfficientNet-B6 (advprop+autoaug)Accuracy - All Images49.6—Unverified
8EfficientNet-B5 (advprop+autoaug)Accuracy - All Images49.1—Unverified
9ViT-16/L-224Accuracy - All Images49—Unverified
10ResNet-50 (gn)Accuracy - All Images48.9—Unverified