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Domain Adaptation

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하위 태스크: 13
평가표: 58
보존된 평가 기록: 391

Domain Adaptation is the task of adapting models across domains. This is motivated by the challenge where the test and training datasets fall from different data distributions due to some factor. Domain adaptation aims to build machine learning models that can be generalized into a target domain and dealing with the discrepancy across domain distributions.

Further readings:

A Brief Review of Domain Adaptation

<span style="color:grey; opacity: 0.6">( Image credit: Unsupervised Image-to-Image Translation Networks )</span>

코드

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

https://github.com/yihong-97/unlock

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Unlocking Constraints: Source-Free Occlusion-Aware Seamless Segmentation

https://github.com/yihongt/dastnet

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Domain Adversarial Spatial-Temporal Network: A Transferable Framework for Short-term Traffic Forecasting across Cities

https://github.com/yihuacheng/puregaze

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PureGaze: Purifying Gaze Feature for Generalizable Gaze Estimation

https://github.com/yinghemedical/imbalance-aware_domain_adaptation

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Addressing Domain Shift via Imbalance-Aware Domain Adaptation in Embryo Development Assessment

https://github.com/yinghui-li-new/dapointr

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DAPoinTr: Domain Adaptive Point Transformer for Point Cloud Completion

https://github.com/yingyichen-cyy/JigsawViT

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Jigsaw-ViT: Learning Jigsaw Puzzles in Vision Transformer

https://github.com/yinjunbo/ssda3d

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SSDA3D: Semi-supervised Domain Adaptation for 3D Object Detection from Point Cloud

https://github.com/yixianqianzy/dpa

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Diverse Preference Augmentation with Multiple Domains for Cold-start Recommendations

https://github.com/yjiangcm/webr

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Instruction-Tuning Data Synthesis from Scratch via Web Reconstruction

https://github.com/yjoh12/cxr-segmentation-by-adain-based-domain-adaptation-and-knowledge-distillation

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CXR Segmentation by AdaIN-based Domain Adaptation and Knowledge Distillation

https://github.com/yjyddq/DLIF

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Generalized Face Anti-spoofing via Finer Domain Partition and Disentangling Liveness-irrelevant Factors

https://github.com/ylily1015/dogetickets

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Doge Tickets: Uncovering Domain-general Language Models by Playing Lottery Tickets

https://github.com/ymoslem/adaptive-mt-llm

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Adaptive Machine Translation with Large Language Models

https://github.com/ymoslem/mt-lm

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Domain-Specific Text Generation for Machine Translation

https://github.com/ymoslem/mt-preparation

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Domain-Specific Text Generation for Machine Translation

https://github.com/ynysjtu/ood_bench

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OoD-Bench: Quantifying and Understanding Two Dimensions of Out-of-Distribution Generalization

https://github.com/yogeshbalaji/Normalized-Wasserstein

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Normalized Wasserstein Distance for Mixture Distributions with Applications in Adversarial Learning and Domain Adaptation

https://github.com/yogeshbalaji/robustOT

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Robust Optimal Transport with Applications in Generative Modeling and Domain Adaptation

https://github.com/yonghaoxu/ut-kd

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Multi-Target Unsupervised Domain Adaptation for Semantic Segmentation without External Data

https://github.com/yonghengsun1997/odada

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Medical Image Segmentation with Domain Adaptation: A Survey

https://github.com/yongsongh/dasrgan

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Texture and Noise Dual Adaptation for Infrared Image Super-Resolution

https://github.com/yore0/ttdg-mgm

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Test-Time Domain Generalization via Universe Learning: A Multi-Graph Matching Approach for Medical Image Segmentation

https://github.com/yorkeyao/VehicleX

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Simulating Content Consistent Vehicle Datasets with Attribute Descent

https://github.com/youngryan1993/PrDA-Progressive-Domain-Adaptation-from-a-Source-Pre-trained-Model

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Domain Adaptation without Source Data

https://github.com/youngryan1993/SFDA-Domain-Adaptation-without-Source-Data

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Domain Adaptation without Source Data

https://github.com/youngryan1993/sfda-sourcefreeda

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Domain Adaptation without Source Data

https://github.com/ypwang61/one-shot-rlvr

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Reinforcement Learning for Reasoning in Large Language Models with One Training Example

https://github.com/yqfang9199/scda

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Source-Free Collaborative Domain Adaptation via Multi-Perspective Feature Enrichment for Functional MRI Analysis

https://github.com/yshen22/FedMM

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FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation

https://github.com/ysj9909/DG-SoRA

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SoRA: Singular Value Decomposed Low-Rank Adaptation for Domain Generalizable Representation Learning

https://github.com/ysu1989/CrossSemparse

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Cross-domain Semantic Parsing via Paraphrasing

https://github.com/ysxcj-hub/cca-lsc

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Contrastive Conditional Alignment based on Label Shift Calibration for Imbalanced Domain Adaptation

https://github.com/yu-rp/distribution-shift-iverson

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Distribution Shift Inversion for Out-of-Distribution Prediction

https://github.com/yu1ut/divergence-optimization

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Noisy Universal Domain Adaptation via Divergence Optimization for Visual Recognition

https://github.com/yuachen/CausalDA

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Domain adaptation under structural causal models

https://github.com/yuan-12138/mi-segnet

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MI-SegNet: Mutual Information-Based US Segmentation for Unseen Domain Generalization

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.