{"total":111,"rows":[{"id":"2112.09133","title":"Masked Feature Prediction for Self-Supervised Visual Pre-Training","created":"2021-12-16","cited_by_count":576,"area":null},{"id":"2110.06207","title":"Open-Set Recognition: a Good Closed-Set Classifier is All You Need?","created":"2021-10-12","cited_by_count":353,"area":null},{"id":"2106.05001","title":"No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data","created":"2021-06-09","cited_by_count":241,"area":null},{"id":"2301.05712","title":"A Survey on Self-supervised Learning: Algorithms, Applications, and Future Trends","created":"2023-01-13","cited_by_count":207,"area":null},{"id":"2205.06743","title":"A Comprehensive Survey of Few-shot Learning: Evolution, Applications, Challenges, and Opportunities","created":"2022-05-13","cited_by_count":163,"area":null},{"id":"2110.03374","title":"Model Adaptation: Historical Contrastive Learning for Unsupervised Domain Adaptation without Source Data","created":"2021-10-07","cited_by_count":152,"area":null},{"id":"2112.10762","title":"StyleSwin: Transformer-based GAN for High-resolution Image Generation","created":"2021-12-20","cited_by_count":152,"area":null},{"id":"2106.05656","title":"MST: Masked Self-Supervised Transformer for Visual Representation","created":"2021-06-10","cited_by_count":114,"area":null},{"id":"2106.11230","title":"Can contrastive learning avoid shortcut solutions?","created":"2021-06-21","cited_by_count":114,"area":null},{"id":"2106.03149","title":"Large-scale Unsupervised Semantic Segmentation","created":"2021-06-06","cited_by_count":101,"area":null},{"id":"2112.13522","title":"Dual Contrastive Learning for General Face Forgery Detection","created":"2021-12-27","cited_by_count":100,"area":null},{"id":"2102.08318","title":"Instance Localization for Self-supervised Detection Pretraining","created":"2021-02-16","cited_by_count":99,"area":null},{"id":"2105.05837","title":"When Does Contrastive Visual Representation Learning Work?","created":"2021-05-12","cited_by_count":92,"area":null},{"id":"2105.08054","title":"Divide and Contrast: Self-supervised Learning from Uncurated Data","created":"2021-05-17","cited_by_count":85,"area":null},{"id":"2103.13517","title":"A Broad Study on the Transferability of Visual Representations with Contrastive Learning","created":"2021-03-24","cited_by_count":78,"area":null},{"id":"2112.09164","title":"High Fidelity Visualization of What Your Self-Supervised Representation Knows About","created":"2021-12-16","cited_by_count":66,"area":null},{"id":"2202.07136","title":"Debiased Self-Training for Semi-Supervised Learning","created":"2022-02-15","cited_by_count":62,"area":null},{"id":"2201.05867","title":"Transferability in Deep Learning: A Survey","created":"2022-01-15","cited_by_count":57,"area":null},{"id":"2306.05067","title":"Improving Visual Prompt Tuning for Self-supervised Vision Transformers","created":"2023-06-08","cited_by_count":57,"area":null},{"id":"2310.05077","title":"FedFed: Feature Distillation against Data Heterogeneity in Federated Learning","created":"2023-10-08","cited_by_count":54,"area":"distill"},{"id":"2207.14381","title":"Pro-tuning: Unified Prompt Tuning for Vision Tasks","created":"2022-07-28","cited_by_count":53,"area":null},{"id":"2206.02465","title":"Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning","created":"2022-06-06","cited_by_count":52,"area":null},{"id":"2107.07746","title":"Rectifying the Shortcut Learning of Background for Few-Shot Learning","created":"2021-07-16","cited_by_count":51,"area":null},{"id":"2109.13228","title":"PASS: An ImageNet replacement for self-supervised pretraining without humans","created":"2021-09-27","cited_by_count":51,"area":null},{"id":"2102.06605","title":"Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning","created":"2021-02-12","cited_by_count":50,"area":null},{"id":"2106.05967","title":"Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations","created":"2021-06-10","cited_by_count":48,"area":null},{"id":"2205.09373","title":"Diversity Matters: Fully Exploiting Depth Clues for Reliable Monocular 3D Object Detection","created":"2022-05-19","cited_by_count":46,"area":null},{"id":"2301.12246","title":"A Closer Look at Few-shot Classification Again","created":"2023-01-28","cited_by_count":46,"area":null},{"id":"2108.02982","title":"Improving Contrastive Learning by Visualizing Feature Transformation","created":"2021-08-06","cited_by_count":44,"area":null},{"id":"2108.11458","title":"Reducing Label Effort: Self-Supervised meets Active Learning","created":"2021-08-25","cited_by_count":42,"area":null},{"id":"2303.05675","title":"HumanBench: Towards General Human-centric Perception with Projector Assisted Pretraining","created":"2023-03-10","cited_by_count":38,"area":null},{"id":"2103.14005","title":"Contrasting Contrastive Self-Supervised Representation Learning Pipelines","created":"2021-03-25","cited_by_count":37,"area":null},{"id":"2201.11736","title":"Ranking Info Noise Contrastive Estimation: Boosting Contrastive Learning via Ranked Positives","created":"2022-01-27","cited_by_count":37,"area":null},{"id":"2112.00496","title":"Revisiting the Transferability of Supervised Pretraining: an MLP Perspective","created":"2021-12-01","cited_by_count":36,"area":null},{"id":"2108.00049","title":"Object-aware Contrastive Learning for Debiased Scene Representation","created":"2021-07-30","cited_by_count":35,"area":null},{"id":"2110.06014","title":"Rethinking Supervised Pre-training for Better Downstream Transferring","created":"2021-10-12","cited_by_count":35,"area":null},{"id":"2204.03946","title":"Probabilistic Representations for Video Contrastive Learning","created":"2022-04-08","cited_by_count":34,"area":null},{"id":"2305.19753","title":"The Tunnel Effect: Building Data Representations in Deep Neural Networks","created":"2023-05-31","cited_by_count":34,"area":null},{"id":"2310.20071","title":"FOCAL: Contrastive Learning for Multimodal Time-Series Sensing Signals in Factorized Orthogonal Latent Space","created":"2023-10-30","cited_by_count":33,"area":null},{"id":"2108.05930","title":"A Systematic Benchmarking Analysis of Transfer Learning for Medical Image Analysis","created":"2021-08-12","cited_by_count":31,"area":null},{"id":"2203.06965","title":"UniVIP: A Unified Framework for Self-Supervised Visual Pre-training","created":"2022-03-14","cited_by_count":31,"area":null},{"id":"2203.17205","title":"Leverage Your Local and Global Representations: A New Self-Supervised Learning Strategy","created":"2022-03-31","cited_by_count":30,"area":null},{"id":"2104.12081","title":"How Well Does Self-Supervised Pre-Training Perform with Streaming Data?","created":"2021-04-25","cited_by_count":29,"area":null},{"id":"2506.09022","title":"Do Multiple Instance Learning Models Transfer?","created":"2025-06-10","cited_by_count":29,"area":null},{"id":"2108.02183","title":"Enhancing Self-supervised Video Representation Learning via Multi-level Feature Optimization","created":"2021-08-04","cited_by_count":27,"area":null},{"id":"2210.07615","title":"FedFM: Anchor-based Feature Matching for Data Heterogeneity in Federated Learning","created":"2022-10-14","cited_by_count":27,"area":null},{"id":"2206.15369","title":"No Reason for No Supervision: Improved Generalization in Supervised Models","created":"2022-06-30","cited_by_count":23,"area":null},{"id":"2303.15466","title":"Supervised Masked Knowledge Distillation for Few-Shot Transformers","created":"2023-03-25","cited_by_count":23,"area":"distill"},{"id":"2206.04667","title":"Extreme Masking for Learning Instance and Distributed Visual Representations","created":"2022-06-09","cited_by_count":21,"area":null},{"id":"2207.09413","title":"SphereFed: Hyperspherical Federated Learning","created":"2022-07-19","cited_by_count":19,"area":null},{"id":"2109.09150","title":"A Study of the Generalizability of Self-Supervised Representations","created":"2021-09-19","cited_by_count":18,"area":null},{"id":"2204.07344","title":"CAiD: Context-Aware Instance Discrimination for Self-supervised Learning in Medical Imaging","created":"2022-04-15","cited_by_count":18,"area":null},{"id":"2401.00416","title":"SVFAP: Self-supervised Video Facial Affect Perceiver","created":"2023-12-31","cited_by_count":18,"area":null},{"id":"2206.05259","title":"Is Self-Supervised Learning More Robust Than Supervised Learning?","created":"2022-06-10","cited_by_count":17,"area":null},{"id":"2401.04614","title":"Generic Knowledge Boosted Pre-training For Remote Sensing Images","created":"2024-01-09","cited_by_count":16,"area":null},{"id":"2207.05340","title":"Dual Contrastive Learning for Spatio-temporal Representation","created":"2022-07-12","cited_by_count":15,"area":null},{"id":"2402.07011","title":"FedImpro: Measuring and Improving Client Update in Federated Learning","created":"2024-02-10","cited_by_count":15,"area":null},{"id":"2405.12368","title":"Layout Agnostic Human Activity Recognition in Smart Homes through Textual Descriptions Of Sensor Triggers (TDOST)","created":"2024-05-20","cited_by_count":13,"area":null},{"id":"2405.15018","title":"What Variables Affect Out-of-Distribution Generalization in Pretrained Models?","created":"2024-05-23","cited_by_count":13,"area":null},{"id":"2205.10110","title":"FedNoiL: A Simple Two-Level Sampling Method for Federated Learning with Noisy Labels","created":"2022-05-20","cited_by_count":12,"area":null},{"id":"2206.04756","title":"An Empirical Study on Disentanglement of Negative-free Contrastive Learning","created":"2022-06-09","cited_by_count":12,"area":null},{"id":"2210.02182","title":"CFL-Net: Image Forgery Localization Using Contrastive Learning","created":"2022-10-04","cited_by_count":12,"area":null},{"id":"2105.02472","title":"XeroAlign: Zero-Shot Cross-lingual Transformer Alignment","created":"2021-05-06","cited_by_count":11,"area":null},{"id":"2205.04771","title":"Domain Invariant Masked Autoencoders for Self-supervised Learning from Multi-domains","created":"2022-05-10","cited_by_count":10,"area":null},{"id":"2210.08909","title":"Watch the Neighbors: A Unified K-Nearest Neighbor Contrastive Learning Framework for OOD Intent Discovery","created":"2022-10-17","cited_by_count":9,"area":null},{"id":"2210.10194","title":"Rethinking Prototypical Contrastive Learning through Alignment, Uniformity and Correlation","created":"2022-10-18","cited_by_count":9,"area":null},{"id":"2211.11116","title":"Structure-Encoding Auxiliary Tasks for Improved Visual Representation in Vision-and-Language Navigation","created":"2022-11-20","cited_by_count":9,"area":null},{"id":"2212.08378","title":"Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning","created":"2022-12-16","cited_by_count":9,"area":null},{"id":"2209.03268","title":"Measuring the Interpretability of Unsupervised Representations via Quantized Reverse Probing","created":"2022-09-07","cited_by_count":8,"area":null},{"id":"2305.12691","title":"Hi-ResNet: Edge Detail Enhancement for High-Resolution Remote Sensing Segmentation","created":"2023-05-22","cited_by_count":8,"area":null},{"id":"2403.13808","title":"On Pretraining Data Diversity for Self-Supervised Learning","created":"2024-03-20","cited_by_count":7,"area":null},{"id":"2406.00535","title":"Causal Contrastive Learning for Counterfactual Regression Over Time","created":"2024-06-01","cited_by_count":7,"area":null},{"id":"2101.08237","title":"An Empirical Study and Analysis on Open-Set Semi-Supervised Learning","created":"2021-01-19","cited_by_count":6,"area":null},{"id":"2101.11058","title":"Supervised Momentum Contrastive Learning for Few-Shot Classification","created":"2021-01-26","cited_by_count":6,"area":null},{"id":"2208.00275","title":"Revisiting the Critical Factors of Augmentation-Invariant Representation Learning","created":"2022-07-30","cited_by_count":6,"area":null},{"id":"2303.15104","title":"Generalizable Local Feature Pre-training for Deformable Shape Analysis","created":"2023-03-27","cited_by_count":6,"area":null},{"id":"2304.04858","title":"Simulated Annealing in Early Layers Leads to Better Generalization","created":"2023-04-10","cited_by_count":6,"area":null},{"id":"2406.02447","title":"Federated Class-Incremental Learning with Hierarchical Generative Prototypes","created":"2024-06-04","cited_by_count":6,"area":null},{"id":"2601.13578","title":"FG-OrIU: Towards Better Forgetting via Feature-Gradient Orthogonality for Incremental Unlearning","created":"2026-01-20","cited_by_count":6,"area":"safety"},{"id":"2108.07582","title":"Self-Supervised Pretraining and Controlled Augmentation Improve Rare Wildlife Recognition in UAV Images","created":"2021-08-17","cited_by_count":5,"area":null},{"id":"2204.08226","title":"Empirical Evaluation and Theoretical Analysis for Representation Learning: A Survey","created":"2022-04-18","cited_by_count":5,"area":null},{"id":"2206.00471","title":"Augmentation Component Analysis: Modeling Similarity via the Augmentation Overlaps","created":"2022-06-01","cited_by_count":5,"area":null},{"id":"2208.00979","title":"Automatically Discovering Novel Visual Categories with Self-supervised Prototype Learning","created":"2022-08-01","cited_by_count":5,"area":null},{"id":"2311.13321","title":"Revisiting Supervision for Continual Representation Learning","created":"2023-11-22","cited_by_count":5,"area":null},{"id":"2206.07125","title":"Self-Supervised Pretraining for Differentially Private Learning","created":"2022-06-14","cited_by_count":4,"area":null},{"id":"2308.13392","title":"Self-Supervised Representation Learning with Cross-Context Learning between Global and Hypercolumn Features","created":"2023-08-25","cited_by_count":4,"area":null},{"id":"2204.03865","title":"Frequency Selective Augmentation for Video Representation Learning","created":"2022-04-08","cited_by_count":3,"area":null},{"id":"2210.05557","title":"OPERA: Omni-Supervised Representation Learning with Hierarchical Supervisions","created":"2022-10-11","cited_by_count":3,"area":null},{"id":"2211.16299","title":"Transferability Estimation Based On Principal Gradient Expectation","created":"2022-11-29","cited_by_count":3,"area":null},{"id":"2108.02798","title":"Self-Supervised Learning from Unlabeled Fundus Photographs Improves Segmentation of the Retina","created":"2021-08-05","cited_by_count":2,"area":null},{"id":"2112.05340","title":"Tradeoffs Between Contrastive and Supervised Learning: An Empirical Study","created":"2021-12-10","cited_by_count":2,"area":null},{"id":"2301.05315","title":"GH-Feat: Learning Versatile Generative Hierarchical Features from GANs","created":"2023-01-12","cited_by_count":2,"area":null},{"id":"2506.03682","title":"How PARTs assemble into wholes: Learning the relative composition of images","created":"2025-06-04","cited_by_count":2,"area":null},{"id":"2508.12108","title":"VELVET-Med: Vision and Efficient Language Pre-training for Volumetric Imaging Tasks in Medicine","created":"2025-08-16","cited_by_count":2,"area":null},{"id":"2110.08851","title":"Unsupervised Representation Learning for Binary Networks by Joint Classifier Learning","created":"2021-10-17","cited_by_count":1,"area":null},{"id":"2201.11388","title":"Contrastive Embedding Distribution Refinement and Entropy-Aware Attention for 3D Point Cloud Classification","created":"2022-01-27","cited_by_count":1,"area":null},{"id":"2210.08819","title":"Correlation between Alignment-Uniformity and Performance of Dense Contrastive Representations","created":"2022-10-17","cited_by_count":1,"area":null},{"id":"2211.05636","title":"Rare Wildlife Recognition with Self-Supervised Representation Learning","created":"2022-10-29","cited_by_count":1,"area":null},{"id":"2308.07580","title":"AutoLTS: Automating Cycling Stress Assessment via Contrastive Learning and Spatial Post-processing","created":"2023-08-15","cited_by_count":1,"area":null},{"id":"2403.17869","title":"To Supervise or Not to Supervise: Understanding and Addressing the Key Challenges of Point Cloud Transfer Learning","created":"2024-03-26","cited_by_count":1,"area":null}],"next_cursor":"100"}