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 776800 of 1751 papers

TitleStatusHype
Adversarial Bayesian Augmentation for Single-Source Domain GeneralizationCode0
Frequency-mixed Single-source Domain Generalization for Medical Image SegmentationCode1
On the Fly Neural Style Smoothing for Risk-Averse Domain GeneralizationCode0
DISPEL: Domain Generalization via Domain-Specific Liberating0
A Causal Framework to Unify Common Domain Generalization Approaches0
Single Domain Generalization via Normalised Cross-correlation Based Convolutions0
Benchmarking Algorithms for Federated Domain GeneralizationCode1
CILF:Causality Inspired Learning Framework for Out-of-Distribution Vehicle Trajectory Prediction0
Towards Generalizable Diabetic Retinopathy Grading in Unseen DomainsCode1
Probabilistic Test-Time Generalization by Variational Neighbor-Labeling0
Domain Generalized Object Detection for Remote Sensing ImagesCode0
Multi-Similarity Contrastive Learning0
Prompting Diffusion Representations for Cross-Domain Semantic SegmentationCode0
Learning Degradation-Independent Representations for Camera ISP Pipelines0
Intra- & Extra-Source Exemplar-Based Style Synthesis for Improved Domain GeneralizationCode1
Learning Content-enhanced Mask Transformer for Domain Generalized Urban-Scene SegmentationCode0
Meta-Reasoning: Semantics-Symbol Deconstruction for Large Language ModelsCode0
MLA-BIN: Model-level Attention and Batch-instance Style Normalization for Domain Generalization of Federated Learning on Medical Image Segmentation0
A Survey on Out-of-Distribution Evaluation of Neural NLP Models0
Adaptive Multi-Modal Cross-Entropy Loss for Stereo MatchingCode1
Chain-of-Thought Prompt Distillation for Multimodal Named Entity Recognition and Multimodal Relation Extraction0
Binary domain generalization for sparsifying binary neural networksCode0
Generalizable Metric Network for Cross-domain Person Re-identification0
MuDPT: Multi-modal Deep-symphysis Prompt Tuning for Large Pre-trained Vision-Language ModelsCode0
Beyond Normal: On the Evaluation of Mutual Information EstimatorsCode1
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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