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 125 of 1751 papers

TitleStatusHype
MoTM: Towards a Foundation Model for Time Series Imputation based on Continuous Modeling0
GLAD: Generalizable Tuning for Vision-Language Models0
Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain GeneralizationCode0
InstructFLIP: Exploring Unified Vision-Language Model for Face Anti-spoofingCode1
From Physics to Foundation Models: A Review of AI-Driven Quantitative Remote Sensing Inversion0
Integrated Structural Prompt Learning for Vision-Language Models0
Feed-Forward SceneDINO for Unsupervised Semantic Scene CompletionCode2
Prompt-Free Conditional Diffusion for Multi-object Image AugmentationCode1
Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations0
Prompt Disentanglement via Language Guidance and Representation Alignment for Domain Generalization0
Generalized Adaptive Transfer Network: Enhancing Transfer Learning in Reinforcement Learning Across DomainsCode0
Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and TransferabilityCode1
FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization0
A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools0
Exploring Graph-Transformer Out-of-Distribution Generalization Abilities0
Rethinking the Role of Operating Conditions for Learning-based Multi-condition Fault Diagnosis0
Domain Generalization for Person Re-identification: A Survey Towards Domain-Agnostic Person MatchingCode1
ConStyX: Content Style Augmentation for Generalizable Medical Image SegmentationCode0
RoCA: Robust Cross-Domain End-to-End Autonomous Driving0
Harmonizing and Merging Source Models for CLIP-based Domain Generalization0
Leveraging Depth and Language for Open-Vocabulary Domain-Generalized Semantic SegmentationCode1
FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient MatchingCode0
Play to Generalize: Learning to Reason Through Game PlayCode2
SurgBench: A Unified Large-Scale Benchmark for Surgical Video Analysis0
Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations0
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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