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 51100 of 1751 papers

TitleStatusHype
Singer Identity Representation Learning using Self-Supervised TechniquesCode2
GLOBEM Dataset: Multi-Year Datasets for Longitudinal Human Behavior Modeling GeneralizationCode2
TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with RecommendationCode2
SyntheX: Scaling Up Learning-based X-ray Image Analysis Through In Silico ExperimentsCode2
Gradient Alignment for Cross-Domain Face Anti-SpoofingCode2
GalLoP: Learning Global and Local Prompts for Vision-Language ModelsCode2
CrossEarth: Geospatial Vision Foundation Model for Domain Generalizable Remote Sensing Semantic SegmentationCode2
Play to Generalize: Learning to Reason Through Game PlayCode2
FAMNet: Frequency-aware Matching Network for Cross-domain Few-shot Medical Image SegmentationCode2
Neural Markov Random Field for Stereo MatchingCode2
Generalized Parametric Contrastive LearningCode2
HPT++: Hierarchically Prompting Vision-Language Models with Multi-Granularity Knowledge Generation and Improved Structure ModelingCode2
Earth-Adapter: Bridge the Geospatial Domain Gaps with Mixture of Frequency AdaptationCode2
DiffusionFake: Enhancing Generalization in Deepfake Detection via Guided Stable DiffusionCode2
A Survey on Domain Generalization for Medical Image AnalysisCode2
EasyPortrait -- Face Parsing and Portrait Segmentation DatasetCode2
Depth Field Networks for Generalizable Multi-view Scene RepresentationCode2
Description and Discussion on DCASE 2024 Challenge Task 2: First-Shot Unsupervised Anomalous Sound Detection for Machine Condition MonitoringCode2
DeepPerception: Advancing R1-like Cognitive Visual Perception in MLLMs for Knowledge-Intensive Visual GroundingCode2
Domain Adaptive and Generalizable Network Architectures and Training Strategies for Semantic Image SegmentationCode2
Diff9D: Diffusion-Based Domain-Generalized Category-Level 9-DoF Object Pose EstimationCode2
Enhance Then Search: An Augmentation-Search Strategy with Foundation Models for Cross-Domain Few-Shot Object DetectionCode2
eCeLLM: Generalizing Large Language Models for E-commerce from Large-scale, High-quality Instruction DataCode2
Feed-Forward SceneDINO for Unsupervised Semantic Scene CompletionCode2
Improving Zero-shot Generalization of Learned Prompts via Unsupervised Knowledge DistillationCode2
Single Domain Generalization for Crowd CountingCode2
Avoiding Shortcuts: Enhancing Channel-Robust Specific Emitter Identification via Single-Source Domain GeneralizationCode2
Generative Medical SegmentationCode2
Building Computationally Efficient and Well-Generalizing Person Re-Identification Models with Metric 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
DART: Diversify-Aggregate-Repeat Training Improves Generalization of Neural NetworksCode1
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
Cross-domain Generalization for AMR ParsingCode1
Cross-Domain Few-Shot Classification via Learned Feature-Wise TransformationCode1
Adaptive Risk Minimization: Learning to Adapt to Domain ShiftCode1
3DLabelProp: Geometric-Driven Domain Generalization for LiDAR Semantic Segmentation in Autonomous DrivingCode1
Cross-Domain Few-Shot Classification via Adversarial Task AugmentationCode1
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable FeaturesCode1
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
Cross Contrasting Feature Perturbation for Domain GeneralizationCode1
Adaptive Methods for Aggregated Domain GeneralizationCode1
Crafting Distribution Shifts for Validation and Training in Single Source Domain GeneralizationCode1
Cross-Domain Ensemble Distillation for Domain GeneralizationCode1
Adaptive High-Frequency Transformer for Diverse Wildlife Re-IdentificationCode1
Consistency-guided Prompt Learning for Vision-Language ModelsCode1
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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