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

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Showing 976–1000 of 1751 papers

TitleStatusHype
Critically examining the Domain Generalizability of Facial Expression Recognition models—0
AtrialGeneral: Domain Generalization for Left Atrial Segmentation of Multi-Center LGE MRIs—0
Attention Bridging Network for Knowledge Transfer—0
Attention Head Purification: A New Perspective to Harness CLIP for Domain Generalization—0
Augmentation-based Domain Generalization for Semantic Segmentation—0
A Unified Framework for Robustness on Diverse Sampling Errors—0
Autonomous Structural Memory Manipulation for Large Language Models Using Hierarchical Embedding Augmentation—0
AXCEL: Automated eXplainable Consistency Evaluation using LLMs—0
Bag of Tricks for Out-of-Distribution Generalization—0
Two-Stage Adaptive Network for Semi-Supervised Cross-Domain Crater Detection under Varying Scenario Distributions—0
Improving Cross-Corpus Speech Emotion Recognition with Adversarial Discriminative Domain Generalization (ADDoG)—0
Batch Normalization Embeddings for Deep Domain Generalization—0
BayeSeg: Bayesian Modeling for Medical Image Segmentation with Interpretable Generalizability—0
Bayesian Domain Invariant Learning via Posterior Generalization of Parameter Distributions—0
Behavioral Priors and Dynamics Models: Improving Performance and Domain Transfer in Offline RL—0
Benchmarking Azerbaijani Neural Machine Translation—0
Benchmarking Cross-Domain Audio-Visual Deception Detection—0
Benchmarking Domain Generalization on EEG-based Emotion Recognition—0
Best sources forward: domain generalization through source-specific nets—0
Better Pseudo-label: Joint Domain-aware Label and Dual-classifier for Semi-supervised Domain Generalization—0
BEV-DG: Cross-Modal Learning under Bird's-Eye View for Domain Generalization of 3D Semantic Segmentation—0
Beyond Domain Adaptation: Unseen Domain Encapsulation via Universal Non-volume Preserving Models—0
Beyond Finite Data: Towards Data-free Out-of-distribution Generalization via Extrapolation—0
Bidirectional Multi-Step Domain Generalization for Visible-Infrared Person Re-Identification—0
Bi-Level Meta-Learning for Few-Shot Domain Generalization—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