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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/nthakur20/income

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Injecting Domain Adaptation with Learning-to-hash for Effective and Efficient Zero-shot Dense Retrieval

https://github.com/nttcslab/dcase2023_task2_baseline_ae

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First-shot anomaly sound detection for machine condition monitoring: A domain generalization baseline

https://github.com/nttrd-mdlab/seld-foa-meir

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Echo-aware Adaptation of Sound Event Localization and Detection in Unknown Environments

https://github.com/nubagcilab/icassp2025-fdgpolyp

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Frequency-Based Federated Domain Generalization for Polyp Segmentation

https://github.com/nudlesoup/first2third-pose

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Enhancing Egocentric 3D Pose Estimation with Third Person Views

https://github.com/nupoorgandhi/data-eff-coref

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Mention Annotations Alone Enable Efficient Domain Adaptation for Coreference Resolution

https://github.com/nupoorgandhi/i2b2-coref-public

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Improving Span Representation for Domain-adapted Coreference Resolution

https://github.com/nvlabs/fan

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Understanding The Robustness in Vision Transformers

https://github.com/nvlabs/gtrs

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Generalized Trajectory Scoring for End-to-end Multimodal Planning

https://github.com/nyquixt/cascadetta

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Adaptive Cascading Network for Continual Test-Time Adaptation

https://github.com/oagarwal/temporal-effects

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Temporal Effects on Pre-trained Models for Language Processing Tasks

https://github.com/observerw/chisellm

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ChiseLLM: Unleashing the Power of Reasoning LLMs for Chisel Agile Hardware Development

https://github.com/oceanypt/CFd

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Feature Adaptation of Pre-Trained Language Models across Languages and Domains with Robust Self-Training

https://github.com/oceanypt/coldqa-tta

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Robust Question Answering against Distribution Shifts with Test-Time Adaptation: An Empirical Study

https://github.com/oceanypt/multi-source-tta

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Multi-Source Test-Time Adaptation as Dueling Bandits for Extractive Question Answering

https://github.com/oezyurty/cluda

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Contrastive Learning for Unsupervised Domain Adaptation of Time Series

https://github.com/oh-yu/domain-invariant-learning

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Two stages domain invariant representation learners solve the large co-variate shift in unsupervised domain adaptation with two dimensional data domains

https://github.com/ohlionel/Prune-Tune

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Finding Sparse Structures for Domain Specific Neural Machine Translation

https://github.com/okojoalg/sequencer

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Sequencer: Deep LSTM for Image Classification

https://github.com/oleffa/laot

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Learning representations that are closed-form Monge mapping optimal with application to domain adaptation

https://github.com/omarmshaal/protobeam

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ProtoBeam: Generalizing Deep Beam Prediction to Unseen Antennas using Prototypical Networks

https://github.com/omggggg/mmdg

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Suppress and Rebalance: Towards Generalized Multi-Modal Face Anti-Spoofing

https://github.com/oneal2000/prag

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Parametric Retrieval Augmented Generation

https://github.com/onlytailei/carla_cil_pytorch

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Visual-based Autonomous Driving Deployment from a Stochastic and Uncertainty-aware Perspective

https://github.com/onuriel/PermutedAdaIN

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Permuted AdaIN: Reducing the Bias Towards Global Statistics in Image Classification

https://github.com/oodbag/rise

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A Sentence Speaks a Thousand Images: Domain Generalization through Distilling CLIP with Language Guidance

https://github.com/oodbag/w2d

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The Two Dimensions of Worst-case Training and the Integrated Effect for Out-of-domain Generalization

https://github.com/open-mmlab/OpenPCDet

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PV-RCNN: The Top-Performing LiDAR-only Solutions for 3D Detection / 3D Tracking / Domain Adaptation of Waymo Open Dataset Challenges

https://github.com/openai/gpt-3

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Language Models are Few-Shot Learners

https://github.com/openbmb/minicpm

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MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

https://github.com/opencv/openvino_training_extensions

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Building Computationally Efficient and Well-Generalizing Person Re-Identification Models with Metric Learning

https://github.com/opengvlab/egovideo

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EgoVideo: Exploring Egocentric Foundation Model and Downstream Adaptation

https://github.com/orange-czh/mamba-sea

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Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation

https://github.com/orion-ai-lab/prototypeinsar

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Learning from Synthetic InSAR with Vision Transformers: The case of volcanic unrest detection

https://github.com/oripress/ccc

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RDumb: A simple approach that questions our progress in continual test-time adaptation

https://github.com/osamazeeshan/subject-based-domain-adaptation-for-fer

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Subject-Based Domain Adaptation for Facial Expression Recognition

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