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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 651–675 of 1751 papers

TitleStatusHype
DADM: Dual Alignment of Domain and Modality for Face Anti-spoofing—0
Chain-of-Thought Matters: Improving Long-Context Language Models with Reasoning Path Supervision—0
Robust sensitivity control in digital pathology via tile score distribution matching—0
Teaching Dense Retrieval Models to Specialize with Listwise Distillation and LLM Data AugmentationCode0
Enhancing 3D Gaze Estimation in the Wild using Weak Supervision with Gaze Following Labels—0
Test-Time Modality Generalization for Medical Image Segmentation—0
MedVLM-R1: Incentivizing Medical Reasoning Capability of Vision-Language Models (VLMs) via Reinforcement Learning—0
Graph Augmentation for Cross Graph Domain Generalization—0
Single Domain Generalization with Model-aware Parametric Batch-wise Mixup—0
A Similarity Paradigm Through Textual Regularization Without Forgetting—0
Evaluating and Enhancing Out-of-Domain Generalization of Task-Oriented Dialog Systems for Task Completion without Turn-level Dialog Annotations—0
GeneralizeFormer: Layer-Adaptive Model Generation across Test-Time Distribution ShiftsCode0
Why Domain Generalization Fail? A View of Necessity and Sufficiency—0
When and How Does CLIP Enable Domain and Compositional Generalization?—0
A Low-Complexity Plug-and-Play Deep Learning Model for Massive MIMO Precoding Across Sites—0
Federated Self-supervised Domain Generalization for Label-efficient Polyp Segmentation—0
Supervised Contrastive Block Disentanglement—0
Color-Quality Invariance for Robust Medical Image SegmentationCode0
Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance—0
Rotation-Adaptive Point Cloud Domain Generalization via Intricate Orientation Learning—0
Multi-Domain Graph Foundation Models: Robust Knowledge Transfer via Topology Alignment—0
Learning to Learn Weight Generation via Local Consistency Diffusion—0
Test-time Loss Landscape Adaptation for Zero-Shot Generalization in Vision-Language Models—0
Intrinsic Tensor Field Propagation in Large Language Models: A Novel Approach to Contextual Information Flow—0
Technical report on label-informed logit redistribution for better domain generalization in low-shot classification with foundation models—0
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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