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 1151–1200 of 1751 papers

TitleStatusHype
Single-domain Generalization in Medical Image Segmentation via Test-time Adaptation from Shape Dictionary—0
Adversarial Consistency for Single Domain Generalization in Medical Image Segmentation—0
Domain Agnostic Few-shot Learning for Speaker Verification—0
Learning with Weak Annotations for Robust Maritime Obstacle DetectionCode1
Gated Domain Units for Multi-source Domain GeneralizationCode0
Domain Generalization with Relaxed Instance Frequency-wise Normalization for Multi-device Acoustic Scene Classification—0
On Certifying and Improving Generalization to Unseen DomainsCode0
Invariant Causal Mechanisms through Distribution Matching—0
Panoramic Panoptic Segmentation: Insights Into Surrounding Parsing for Mobile Agents via Unsupervised Contrastive LearningCode1
Mitigating Data Heterogeneity in Federated Learning with Data AugmentationCode1
Test-time image-to-image translation ensembling improves out-of-distribution generalization in histopathology—0
0/1 Deep Neural Networks via Block Coordinate Descent—0
Towards Generalizable Person Re-identification with a Bi-stream Generative Model—0
Finding Diverse and Predictable Subgraphs for Graph Domain Generalization—0
Self-Supervised Learning for Videos: A SurveyCode0
The Importance of Background Information for Out of Distribution Generalization—0
Learning Fair Representation via Distributional Contrastive DisentanglementCode1
Domain Generalization via Selective Consistency Regularization for Time Series Classification—0
Improving generalization by mimicking the human visual dietCode0
Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization—0
Improving Diversity with Adversarially Learned Transformations for Domain GeneralizationCode1
Slimmable Domain AdaptationCode0
INDIGO: Intrinsic Multimodality for Domain Generalization—0
Description and Discussion on DCASE 2022 Challenge Task 2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring Applying Domain Generalization TechniquesCode1
SyntheX: Scaling Up Learning-based X-ray Image Analysis Through In Silico ExperimentsCode2
Improving Pre-trained Language Model Fine-tuning with Noise Stability Regularization—0
APT-36K: A Large-scale Benchmark for Animal Pose Estimation and TrackingCode1
Toward Real-world Single Image Deraining: A New Benchmark and BeyondCode1
Referring Image MattingCode2
Causal Balancing for Domain GeneralizationCode1
Sparse Mixture-of-Experts are Domain Generalizable LearnersCode1
OneRing: A Simple Method for Source-free Open-partial Domain AdaptationCode1
Using Representation Expressiveness and Learnability to Evaluate Self-Supervised Learning Methods—0
Evolving Domain Generalization—0
Contrastive Centroid Supervision Alleviates Domain Shift in Medical Image Classification—0
Dynamic Domain GeneralizationCode1
MIMII DG: Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection for Domain Generalization TaskCode1
FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias ReductionCode1
Supporting Vision-Language Model Inference with Causality-pruning Knowledge Prompt—0
Temporal Domain Generalization with Drift-Aware Dynamic Neural NetworksCode1
Test-time Batch Normalization—0
Generalizing to Evolving Domains with Latent Structure-Aware Sequential AutoencoderCode0
Not to Overfit or Underfit the Source Domains? An Empirical Study of Domain Generalization in Question Answering—0
Test-time Fourier Style Calibration for Domain GeneralizationCode1
Contrastive Domain Disentanglement for Generalizable Medical Image Segmentation—0
Localized Adversarial Domain GeneralizationCode1
Invariant Content Synergistic Learning for Domain Generalization of Medical Image Segmentation—0
InvNorm: Domain Generalization for Object Detection in Gastrointestinal Endoscopy—0
EllSeg-Gen, towards Domain Generalization for head-mounted eyetrackingCode0
Sequencer: Deep LSTM for Image ClassificationCode5
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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