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 1–50 of 1751 papers

TitleStatusHype
DINOv2: Learning Robust Visual Features without SupervisionCode6
A ConvNet for the 2020sCode5
Sequencer: Deep LSTM for Image ClassificationCode5
Matching Anything by Segmenting AnythingCode5
Delving into RL for Image Generation with CoT: A Study on DPO vs. GRPOCode4
Conditional Prompt Learning for Vision-Language ModelsCode4
Seg-Zero: Reasoning-Chain Guided Segmentation via Cognitive ReinforcementCode4
Deep Residual Learning for Image RecognitionCode4
Light-R1: Curriculum SFT, DPO and RL for Long COT from Scratch and BeyondCode4
MetaFormer Baselines for VisionCode3
Generative Data Augmentation using LLMs improves Distributional Robustness in Question AnsweringCode3
Stronger Fewer & Superior: Harnessing Vision Foundation Models for Domain Generalized Semantic SegmentationCode3
Distilling LLM Agent into Small Models with Retrieval and Code ToolsCode3
Generalized Trajectory Scoring for End-to-end Multimodal PlanningCode3
Reinforcement Learning for Reasoning in Large Language Models with One Training ExampleCode3
AutoAugment: Learning Augmentation Policies from DataCode3
EfficientNet: Rethinking Model Scaling for Convolutional Neural NetworksCode3
Advances in Multimodal Adaptation and Generalization: From Traditional Approaches to Foundation ModelsCode3
ControlMLLM: Training-Free Visual Prompt Learning for Multimodal Large Language ModelsCode3
Mamba as a Bridge: Where Vision Foundation Models Meet Vision Language Models for Domain-Generalized Semantic SegmentationCode2
Improving Zero-shot Generalization of Learned Prompts via Unsupervised Knowledge DistillationCode2
MMA: Multi-Modal Adapter for Vision-Language ModelsCode2
A Survey on Domain Generalization for Medical Image AnalysisCode2
Gradient Alignment for Cross-Domain Face Anti-SpoofingCode2
Generalized Parametric Contrastive LearningCode2
GLOBEM Dataset: Multi-Year Datasets for Longitudinal Human Behavior Modeling GeneralizationCode2
Generative Medical SegmentationCode2
Learning to Prompt for Vision-Language ModelsCode2
HPT++: Hierarchically Prompting Vision-Language Models with Multi-Granularity Knowledge Generation and Improved Structure ModelingCode2
Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference timeCode2
EasyPortrait -- Face Parsing and Portrait Segmentation DatasetCode2
Earth-Adapter: Bridge the Geospatial Domain Gaps with Mixture of Frequency AdaptationCode2
Enhance Then Search: An Augmentation-Search Strategy with Foundation Models for Cross-Domain Few-Shot Object DetectionCode2
DiffusionFake: Enhancing Generalization in Deepfake Detection via Guided Stable DiffusionCode2
Depth Field Networks for Generalizable Multi-view Scene RepresentationCode2
FAMNet: Frequency-aware Matching Network for Cross-domain Few-shot Medical Image SegmentationCode2
CrossEarth: Geospatial Vision Foundation Model for Domain Generalizable Remote Sensing Semantic SegmentationCode2
Adversarial Supervision Makes Layout-to-Image Diffusion Models ThriveCode2
Continuous Temporal Domain GeneralizationCode2
DatasetDM: Synthesizing Data with Perception Annotations Using Diffusion ModelsCode2
Description and Discussion on DCASE 2024 Challenge Task 2: First-Shot Unsupervised Anomalous Sound Detection for Machine Condition MonitoringCode2
Diff9D: Diffusion-Based Domain-Generalized Category-Level 9-DoF Object Pose EstimationCode2
Building Computationally Efficient and Well-Generalizing Person Re-Identification Models with Metric LearningCode2
Domain Adaptive and Generalizable Network Architectures and Training Strategies for Semantic Image SegmentationCode2
Benchmarking Neural Network Robustness to Common Corruptions and PerturbationsCode2
eCeLLM: Generalizing Large Language Models for E-commerce from Large-scale, High-quality Instruction DataCode2
CLIP-Powered Domain Generalization and Domain Adaptation: A Comprehensive SurveyCode2
GalLoP: Learning Global and Local Prompts for Vision-Language ModelsCode2
Avoiding Shortcuts: Enhancing Channel-Robust Specific Emitter Identification via Single-Source Domain GeneralizationCode2
BatchFormer: Learning to Explore Sample Relationships for Robust Representation LearningCode2
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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