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 51–100 of 1751 papers

TitleStatusHype
Pedestrian Detection: Domain Generalization, CNNs, Transformers and BeyondCode2
Avoiding Shortcuts: Enhancing Channel-Robust Specific Emitter Identification via Single-Source Domain GeneralizationCode2
Single Domain Generalization for Crowd CountingCode2
HPT++: Hierarchically Prompting Vision-Language Models with Multi-Granularity Knowledge Generation and Improved Structure ModelingCode2
GLOBEM Dataset: Multi-Year Datasets for Longitudinal Human Behavior Modeling GeneralizationCode2
Improving Zero-shot Generalization of Learned Prompts via Unsupervised Knowledge DistillationCode2
Generalized Parametric Contrastive LearningCode2
Benchmarking Neural Network Robustness to Common Corruptions and PerturbationsCode2
Enhance Then Search: An Augmentation-Search Strategy with Foundation Models for Cross-Domain Few-Shot Object DetectionCode2
On the limits of cross-domain generalization in automated X-ray predictionCode2
DatasetDM: Synthesizing Data with Perception Annotations Using Diffusion ModelsCode2
On-Device Domain GeneralizationCode2
Feed-Forward SceneDINO for Unsupervised Semantic Scene CompletionCode2
Learning to Prompt for Vision-Language ModelsCode2
Domain Adaptive and Generalizable Network Architectures and Training Strategies for Semantic Image SegmentationCode2
EasyPortrait -- Face Parsing and Portrait Segmentation DatasetCode2
DiffusionFake: Enhancing Generalization in Deepfake Detection via Guided Stable DiffusionCode2
eCeLLM: Generalizing Large Language Models for E-commerce from Large-scale, High-quality Instruction DataCode2
Depth Field Networks for Generalizable Multi-view Scene RepresentationCode2
Earth-Adapter: Bridge the Geospatial Domain Gaps with Mixture of Frequency AdaptationCode2
Description and Discussion on DCASE 2024 Challenge Task 2: First-Shot Unsupervised Anomalous Sound Detection for Machine Condition MonitoringCode2
FAMNet: Frequency-aware Matching Network for Cross-domain Few-shot Medical Image SegmentationCode2
DeepPerception: Advancing R1-like Cognitive Visual Perception in MLLMs for Knowledge-Intensive Visual GroundingCode2
GalLoP: Learning Global and Local Prompts for Vision-Language ModelsCode2
Diff9D: Diffusion-Based Domain-Generalized Category-Level 9-DoF Object Pose EstimationCode2
Generative Medical SegmentationCode2
Gradient Alignment for Cross-Domain Face Anti-SpoofingCode2
Building Computationally Efficient and Well-Generalizing Person Re-Identification Models with Metric LearningCode2
SoRA: Singular Value Decomposed Low-Rank Adaptation for Domain Generalizable Representation LearningCode2
MAPSeg: Unified Unsupervised Domain Adaptation for Heterogeneous Medical Image Segmentation Based on 3D Masked Autoencoding and Pseudo-LabelingCode1
UniDA3D: Unified Domain Adaptive 3D Semantic Segmentation PipelineCode1
Benchmarking Distribution Shift in Tabular Data with TableShiftCode1
A Closer Look at Few-shot ClassificationCode1
DART: Open-Domain Structured Data Record to Text GenerationCode1
DATTA: Domain-Adversarial Test-Time Adaptation for Cross-Domain WiFi-Based Human Activity RecognitionCode1
Benchmarking Algorithms for Federated Domain GeneralizationCode1
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable FeaturesCode1
Adaptive Risk Minimization: Learning to Adapt to Domain ShiftCode1
3DLabelProp: Geometric-Driven Domain Generalization for LiDAR Semantic Segmentation in Autonomous DrivingCode1
DART: Diversify-Aggregate-Repeat Training Improves Generalization of Neural NetworksCode1
DecAug: Out-of-Distribution Generalization via Decomposed Feature Representation and Semantic AugmentationCode1
Adaptive Network Combination for Single-Image Reflection Removal: A Domain Generalization PerspectiveCode1
A Circuit Domain Generalization Framework for Efficient Logic Synthesis in Chip DesignCode1
Bag of Tricks for Image Classification with Convolutional Neural NetworksCode1
Cross-Domain Few-Shot Classification via Adversarial Task AugmentationCode1
Adaptive Methods for Aggregated Domain GeneralizationCode1
Cross-Domain Few-Shot Classification via Learned Feature-Wise TransformationCode1
Cross-domain Generalization for AMR ParsingCode1
Adaptive High-Frequency Transformer for Diverse Wildlife Re-IdentificationCode1
AutoGPart: Intermediate Supervision Search for Generalizable 3D Part SegmentationCode1
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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