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Domain Generalization

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하위 태스크: 3
평가표: 21
보존된 평가 기록: 570

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

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/hendrycks/natural-adv-examples

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Natural Adversarial Examples

https://github.com/hendrycks/robustness

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Benchmarking Neural Network Robustness to Common Corruptions and Perturbations

https://github.com/henrikmarklund/arm

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Adaptive Risk Minimization: Learning to Adapt to Domain Shift

https://github.com/hik-lab/slimda

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Slimmable Domain Adaptation

https://github.com/hiker-lw/realrain-1k

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Toward Real-world Single Image Deraining: A New Benchmark and Beyond

https://github.com/hikvision-research/domaingeneralization

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Attention Diversification for Domain Generalization

https://github.com/hilab-git/dag4mia

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CDDSA: Contrastive Domain Disentanglement and Style Augmentation for Generalizable Medical Image Segmentation

https://github.com/hilab-git/dca-net

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Domain Composition and Attention for Unseen-Domain Generalizable Medical Image Segmentation

https://github.com/hkust-knowcomp/pseudoreasoner

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PseudoReasoner: Leveraging Pseudo Labels for Commonsense Knowledge Base Population

https://github.com/hkust-nlp/universal_truthfulness_hyperplane

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On the Universal Truthfulness Hyperplane Inside LLMs

https://github.com/hlzhang109/ddg

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Towards Principled Disentanglement for Domain Generalization

https://github.com/hosseinshn/DGSML

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Domain Generalization via Semi-supervised Meta Learning

https://github.com/hpzhang94/DomainSum

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DomainSum: A Hierarchical Benchmark for Fine-Grained Domain Shift in Abstractive Text Summarization

https://github.com/hrlblab/IRS

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IRS: Incremental Relationship-guided Segmentation for Digital Pathology

https://github.com/hrlblab/layer_segmentation

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Cross-Species Data Integration for Enhanced Layer Segmentation in Kidney Pathology

https://github.com/huanranchen/ASRNorm

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AFN: Adaptive Fusion Normalization via an Encoder-Decoder Framework

https://github.com/huawei-noah/federated-learning

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Understanding Hessian Alignment for Domain Generalization

https://github.com/huaxiuyao/TALLY

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Multi-Domain Long-Tailed Learning by Augmenting Disentangled Representations

https://github.com/huaxiuyao/wild-time

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Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time

https://github.com/huiqianli/asps

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ASPS: Augmented Segment Anything Model for Polyp Segmentation

https://github.com/hukenovs/easyportrait

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EasyPortrait -- Face Parsing and Portrait Segmentation Dataset

https://github.com/hytseng0509/CrossDomainFewShot

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Cross-Domain Few-Shot Classification via Learned Feature-Wise Transformation

https://github.com/hytseng0509/DropGrad

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Regularizing Meta-Learning via Gradient Dropout

https://github.com/iCGY96/APR

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Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency Domain

https://github.com/ianxmason/compositional-robustness

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Modularity Trumps Invariance for Compositional Robustness

https://github.com/ibtihalferwana/pirm

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Learning Optimal Features via Partial Invariance

https://github.com/idea-iitd/grail

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GRAIL: Graph Edit Distance and Node Alignment Using LLM-Generated Code

https://github.com/ieee8023/xray-generalization

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On the limits of cross-domain generalization in automated X-ray prediction

https://github.com/ifnspaml/revt

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A Re-Parameterized Vision Transformer (ReVT) for Domain-Generalized Semantic Segmentation

https://github.com/im-ethz/pub-gdu4dg

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Gated Domain Units for Multi-source Domain Generalization

https://github.com/ink-usc/sparse-distillation

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Sparse Distillation: Speeding Up Text Classification by Using Bigger Student Models

https://github.com/inouye-lab/feddg_benchmark

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Benchmarking Algorithms for Federated Domain Generalization

https://github.com/invictus717/UniDG

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Towards Unified and Effective Domain Generalization

https://github.com/jaeill/CVPR23-VNE

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VNE: An Effective Method for Improving Deep Representation by Manipulating Eigenvalue Distribution

https://github.com/janesjanes/sketchy

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Deep Shape Matching

https://github.com/jaychempan/ETS

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Enhance Then Search: An Augmentation-Search Strategy with Foundation Models for Cross-Domain Few-Shot Object Detection

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