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Domain Adaptation

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하위 태스크: 13
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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/shaoshitong/NICO

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Bootstrap Generalization Ability from Loss Landscape Perspective

https://github.com/shaoyuanlo/artuda

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Exploring Adversarially Robust Training for Unsupervised Domain Adaptation

https://github.com/shaoyuanlo/stpl

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Spatio-Temporal Pixel-Level Contrastive Learning-based Source-Free Domain Adaptation for Video Semantic Segmentation

https://github.com/sharat29ag/contextual_class

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Reducing Annotation Effort by Identifying and Labeling Contextually Diverse Classes for Semantic Segmentation Under Domain Shift

https://github.com/sharonchokuwa/VAE-DG

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Generalizing Across Domains in Diabetic Retinopathy via Variational Autoencoders

https://github.com/sharonchokuwa/dg-adr

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Divergent Domains, Convergent Grading: Enhancing Generalization in Diabetic Retinopathy Grading

https://github.com/shayangharib/AUDASC

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Unsupervised adversarial domain adaptation for acoustic scene classification

https://github.com/sheepooo/pit-position-invariant-transform

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PIT: Position-Invariant Transform for Cross-FoV Domain Adaptation

https://github.com/shengcailiao/QAConv

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Interpretable and Generalizable Person Re-Identification with Query-Adaptive Convolution and Temporal Lifting

https://github.com/shengcao-cao/cmt

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Contrastive Mean Teacher for Domain Adaptive Object Detectors

https://github.com/shengcheng/aba

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Adversarial Bayesian Augmentation for Single-Source Domain Generalization

https://github.com/shengkuangcn/mscda

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MSCDA: Multi-level Semantic-guided Contrast Improves Unsupervised Domain Adaptation for Breast MRI Segmentation in Small Datasets

https://github.com/shenxiaocam/ACDNE

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Adversarial Deep Network Embedding for Cross-network Node Classification

https://github.com/shenxiaocam/dm_gnn

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Domain-adaptive Message Passing Graph Neural Network

https://github.com/shenzheng2000/instance-warp

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Instance-Warp: Saliency Guided Image Warping for Unsupervised Domain Adaptation

https://github.com/shi-labs/diffusion-driven-test-time-adaptation-via-synthetic-domain-alignment

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Everything to the Synthetic: Diffusion-driven Test-time Adaptation via Synthetic-Domain Alignment

https://github.com/shigemichimatsuzaki/ms2pl

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Multi-Source Soft Pseudo-Label Learning with Domain Similarity-based Weighting for Semantic Segmentation

https://github.com/shimmer93/mpcount

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Single Domain Generalization for Crowd Counting

https://github.com/shinyflight/sfda2

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SF(DA)$^2$: Source-free Domain Adaptation Through the Lens of Data Augmentation

https://github.com/shiralab/opendg-eval

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Simple Domain Generalization Methods are Strong Baselines for Open Domain Generalization

https://github.com/shishicode/agot

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Soft-Prompting with Graph-of-Thought for Multi-modal Representation Learning

https://github.com/shishuaihu/ccsdg

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Devil is in Channels: Contrastive Single Domain Generalization for Medical Image Segmentation

https://github.com/shishuaihu/prosfda

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ProSFDA: Prompt Learning based Source-free Domain Adaptation for Medical Image Segmentation

https://github.com/shiyegao/DDA

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Back to the Source: Diffusion-Driven Test-Time Adaptation

https://github.com/shogi880/DPLCLIP

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Domain Prompt Learning for Efficiently Adapting CLIP to Unseen Domains

https://github.com/showlab/datasetdm

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DatasetDM: Synthesizing Data with Perception Annotations Using Diffusion Models

https://github.com/showlab/doracycle

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DoraCycle: Domain-Oriented Adaptation of Unified Generative Model in Multimodal Cycles

https://github.com/showlab/macosworld

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macOSWorld: A Multilingual Interactive Benchmark for GUI Agents

https://github.com/showlab/sct

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SCT: A Simple Baseline for Parameter-Efficient Fine-Tuning via Salient Channels

https://github.com/shreyasrajesh/DA-Object-Detection

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Domain Adaptation for Object Detection using SE Adaptors and Center Loss

https://github.com/shreydesai/adaptive-ensembling

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Adaptive Ensembling: Unsupervised Domain Adaptation for Political Document Analysis

https://github.com/shuailyu/reb

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REB: Reducing Biases in Representation for Industrial Anomaly Detection

https://github.com/shuolucs/awesome-out-of-distribution-detection

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Recent Advances in OOD Detection: Problems and Approaches

https://github.com/shutakahama/DAMIL

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Domain Adaptive Multiple Instance Learning for Instance-level Prediction of Pathological Images

https://github.com/shuvenduroy/coprompt

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Consistency-guided Prompt Learning for Vision-Language Models

https://github.com/shuxy0120/adatriplet-ra

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AdaTriplet-RA: Domain Matching via Adaptive Triplet and Reinforced Attention for Unsupervised Domain Adaptation

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