Transfer Learning

Transfer Learning is a machine learning technique where a model trained on one task is re-purposed and fine-tuned for a related, but different task. The idea behind transfer learning is to leverage the knowledge learned from a pre-trained model to solve a new, but related problem. This can be useful in situations where there is limited data available to train a new model from scratch, or when the new task is similar enough to the original task that the pre-trained model can be adapted to the new problem with only minor modifications.

( Image credit: Subodh Malgonde )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1276–1300 of 10307 papers

Title	Date	Tasks	Status	Hype
Graphical Object Detection in Document Images	Aug 25, 2020	Domain AdaptationObject	CodeCode Available	1
Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis	Oct 31, 2023	Transfer Learning	CodeCode Available	1
Graphonomy: Universal Human Parsing via Graph Transfer Learning	Apr 9, 2019	Human ParsingTransfer Learning	CodeCode Available	1
Bayesian Optimization with Automatic Prior Selection for Data-Efficient Direct Policy Search	Sep 20, 2017	Bayesian OptimizationTransfer Learning	CodeCode Available	1
HAKE: Human Activity Knowledge Engine	Apr 13, 2019	Action DetectionHuman-Object Interaction Detection	CodeCode Available	1
Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning	Jan 10, 2022	Transfer Learning	CodeCode Available	1
HEAD: HEtero-Assists Distillation for Heterogeneous Object Detectors	Jul 12, 2022	Knowledge DistillationObject	CodeCode Available	1
Heterogeneous Graph Contrastive Learning for Recommendation	Mar 2, 2023	Contrastive LearningRecommendation Systems	CodeCode Available	1
Different Set Domain Adaptation for Brain-Computer Interfaces: A Label Alignment Approach	Dec 3, 2019	Brain Computer InterfaceDomain Adaptation	CodeCode Available	1
A Strong and Simple Deep Learning Baseline for BCI MI Decoding	Sep 11, 2023	Deep LearningEEG	CodeCode Available	1
Hi-End-MAE: Hierarchical encoder-driven masked autoencoders are stronger vision learners for medical image segmentation	Feb 12, 2025	Computational EfficiencyImage Segmentation	CodeCode Available	1
CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning	Oct 8, 2020	Reinforcement Learning (RL)Transfer Learning	CodeCode Available	1
HiNet: Novel Multi-Scenario & Multi-Task Learning with Hierarchical Information Extraction	Mar 10, 2023	Multi-Task LearningRecommendation Systems	CodeCode Available	1
HiViT: Hierarchical Vision Transformer Meets Masked Image Modeling	May 30, 2022	Transfer Learning	CodeCode Available	1
HOICLIP: Efficient Knowledge Transfer for HOI Detection with Vision-Language Models	Mar 28, 2023	DecoderHuman-Object Interaction Detection	CodeCode Available	1
CARLANE: A Lane Detection Benchmark for Unsupervised Domain Adaptation from Simulation to multiple Real-World Domains	Jun 16, 2022	2D Semantic SegmentationAutonomous Driving	CodeCode Available	1
Can LLM Watermarks Robustly Prevent Unauthorized Knowledge Distillation?	Feb 17, 2025	Knowledge DistillationLanguage Modeling	CodeCode Available	1
HPO-B: A Large-Scale Reproducible Benchmark for Black-Box HPO based on OpenML	Jun 11, 2021	Hyperparameter OptimizationTransfer Learning	CodeCode Available	1
A benchmark dataset for deep learning-based airplane detection: HRPlanes	Apr 22, 2022	Deep Learningobject-detection	CodeCode Available	1
Hydra: A System for Large Multi-Model Deep Learning	Oct 16, 2021	Deep LearningGPU	CodeCode Available	1
Transferring Unconditional to Conditional GANs with Hyper-Modulation	Dec 4, 2021	Conditional Image GenerationContrastive Learning	CodeCode Available	1
Hyper-Representations for Pre-Training and Transfer Learning	Jul 22, 2022	Knowledge DistillationNeural Architecture Search	CodeCode Available	1
Hyper-Representations: Learning from Populations of Neural Networks	Oct 7, 2024	Representation LearningTransfer Learning	CodeCode Available	1
I2I: Initializing Adapters with Improvised Knowledge	Apr 4, 2023	Continual LearningQuestion Answering	CodeCode Available	1
CEM500K – A large-scale heterogeneous unlabeled cellular electron microscopy image dataset for deep learning	Dec 11, 2020	Electron Microscopy Image SegmentationSegmentation	CodeCode Available	1

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All datasets Office-Home 100 sleep nights of 8 caregivers BanglaLekha Isolated Dataset COCO70 KITTI Object Tracking Evaluation 2012 Retinal Fundus MultiDisease Image Dataset (RFMiD)

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	APCLIP	Accuracy	84.2	—	Unverified
2	DFA-ENT	Accuracy	69.2	—	Unverified
3	DFA-SAFN	Accuracy	69.1	—	Unverified
4	EasyTL	Accuracy	63.3	—	Unverified
5	MEDA	Accuracy	60.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CNN	10-20% Mask PSNR	3.23	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Chatterjee, Dutta et al.[1]	Accuracy	96.12	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Co-Tuning	Accuracy	85.65	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Physical Access	EER	5.74	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	riadd.aucmedi	AUROC	0.95	—	Unverified