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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/miccai2023anony/renalvesselseg

공식 코드

Extremely weakly-supervised blood vessel segmentation with physiologically based synthesis and domain adaptation

https://github.com/miccunifi/kdpl

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Improving Zero-shot Generalization of Learned Prompts via Unsupervised Knowledge Distillation

https://github.com/michaelliyunhao/skeleton2humanoid

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Skeleton2Humanoid: Animating Simulated Characters for Physically-plausible Motion In-betweening

https://github.com/michetonu/DA-RNN_manoeuver_anticipation

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Robust and Subject-Independent Driving Manoeuvre Anticipation through Domain-Adversarial Recurrent Neural Networks

https://github.com/michiganleon/reclip_wacv

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ReCLIP: Refine Contrastive Language Image Pre-Training with Source Free Domain Adaptation

https://github.com/michiyasunaga/bifi

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Break-It-Fix-It: Unsupervised Learning for Program Repair

https://github.com/michuanhaohao/transreid-ssl

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Self-Supervised Pre-Training for Transformer-Based Person Re-Identification

https://github.com/microsoft/ProDA

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Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation

https://github.com/microsoft/S2R-DepthNet

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S2R-DepthNet: Learning a Generalizable Depth-specific Structural Representation

https://github.com/microsoft/SNR

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Style Normalization and Restitution for Generalizable Person Re-identification

https://github.com/microsoft/UDA

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ToAlign: Task-oriented Alignment for Unsupervised Domain Adaptation

https://github.com/microsoft/lmops

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Improving Domain Adaptation through Extended-Text Reading Comprehension

https://github.com/microsoft/robustdg

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Domain Generalization using Causal Matching

https://github.com/microsoft/unilm

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Discriminative Adversarial Search for Abstractive Summarization

https://github.com/midas-research/randomlaynet

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RanLayNet: A Dataset for Document Layout Detection used for Domain Adaptation and Generalization

https://github.com/miemieyanga/ResiDualGAN-DRDG

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ResiDualGAN: Resize-Residual DualGAN for Cross-Domain Remote Sensing Images Semantic Segmentation

https://github.com/mihirp1998/Slot-TTA

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Test-time Adaptation with Slot-Centric Models

https://github.com/mil-tokyo/MCD_DA

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Maximum Classifier Discrepancy for Unsupervised Domain Adaptation

https://github.com/mil-tokyo/dg_mmld

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Domain Generalization Using a Mixture of Multiple Latent Domains

https://github.com/mims-harvard/raincoat

공식 코드

Domain Adaptation for Time Series Under Feature and Label Shifts

https://github.com/mims-harvard/tfc-pretraining

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Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency

https://github.com/mindflow-institue/awesome-implicit-neural-representations-in-medical-imaging

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Implicit Neural Representation in Medical Imaging: A Comparative Survey

https://github.com/mingjiewang0606/lcye-attack_reid

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Look Closer to Your Enemy: Learning to Attack via Teacher-Student Mimicking

https://github.com/mingukjang/tast

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Test-Time Adaptation via Self-Training with Nearest Neighbor Information

https://github.com/mingxuangu/few-shot-uda

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Few-shot Unsupervised Domain Adaptation for Multi-modal Cardiac Image Segmentation

https://github.com/mingyuliutw/CoGAN

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Coupled Generative Adversarial Networks

https://github.com/mingyuliutw/UNIT

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Unsupervised Image-to-Image Translation Networks

https://github.com/minjiyoon/ktn

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Zero-shot Transfer Learning within a Heterogeneous Graph via Knowledge Transfer Networks

https://github.com/minsu-kim320/Cross-Domain-Grouping-and-Alignment-for-Domain-Adaptive-Semantic-Segmentation

공식 코드

Cross-Domain Grouping and Alignment for Domain Adaptive Semantic Segmentation

https://github.com/mir-mu/softalign_objectives

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Soft Alignment Objectives for Robust Adaptation of Language Generation

https://github.com/miralab-ustc/ai4logicsynthesis-prunex

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A Circuit Domain Generalization Framework for Efficient Logic Synthesis in Chip Design

https://github.com/mirkes/dapca

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Domain Adaptation Principal Component Analysis: base linear method for learning with out-of-distribution data

https://github.com/mirunabetianu/dallmi

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DALLMi: Domain Adaption for LLM-based Multi-label Classifier

https://github.com/misonsky/Amdg

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A Unified Data Augmentation Framework for Low-Resource Multi-Domain Dialogue Generation

https://github.com/mit-ll/robust-vision-language-finetuning

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Robust Fine-Tuning of Vision-Language Models for Domain Generalization

https://github.com/mitchfuchs/chimpbehave

공식 코드

From Forest to Zoo: Great Ape Behavior Recognition with ChimpBehave

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