{"total":51,"rows":[{"id":"2306.00989","title":"Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles","created":"2023-06-01","cited_by_count":290,"area":null},{"id":"2304.12210","title":"A Cookbook of Self-Supervised Learning","created":"2023-04-24","cited_by_count":250,"area":null},{"id":"2208.00173","title":"A Survey on Masked Autoencoder for Self-supervised Learning in Vision and Beyond","created":"2022-07-30","cited_by_count":58,"area":null},{"id":"2304.05919","title":"Hard Patches Mining for Masked Image Modeling","created":"2023-04-12","cited_by_count":57,"area":null},{"id":"2205.13137","title":"MixMAE: Mixed and Masked Autoencoder for Efficient Pretraining of Hierarchical Vision Transformers","created":"2022-05-26","cited_by_count":47,"area":null},{"id":"2303.05251","title":"Masked Image Modeling with Local Multi-Scale Reconstruction","created":"2023-03-09","cited_by_count":43,"area":null},{"id":"2304.11523","title":"TransFlow: Transformer as Flow Learner","created":"2023-04-23","cited_by_count":32,"area":null},{"id":"2308.16572","title":"CL-MAE: Curriculum-Learned Masked Autoencoders","created":"2023-08-31","cited_by_count":22,"area":null},{"id":"2408.01946","title":"Masked Angle-Aware Autoencoder for Remote Sensing Images","created":"2024-08-04","cited_by_count":22,"area":null},{"id":"2309.03576","title":"DropPos: Pre-Training Vision Transformers by Reconstructing Dropped Positions","created":"2023-09-07","cited_by_count":19,"area":null},{"id":"2308.04829","title":"MixReorg: Cross-Modal Mixed Patch Reorganization is a Good Mask Learner for Open-World Semantic Segmentation","created":"2023-08-09","cited_by_count":18,"area":null},{"id":"2310.20704","title":"Limited Data, Unlimited Potential: A Study on ViTs Augmented by Masked Autoencoders","created":"2023-10-31","cited_by_count":17,"area":null},{"id":"2409.13366","title":"RingMo-Aerial: An Aerial Remote Sensing Foundation Model With Affine Transformation Contrastive Learning","created":"2024-09-20","cited_by_count":15,"area":null},{"id":"2401.00897","title":"Masked Modeling for Self-supervised Representation Learning on Vision and Beyond","created":"2023-12-31","cited_by_count":13,"area":null},{"id":"2303.05475","title":"Mimic before Reconstruct: Enhancing Masked Autoencoders with Feature Mimicking","created":"2023-03-09","cited_by_count":12,"area":null},{"id":"2402.00407","title":"InfMAE: A Foundation Model in the Infrared Modality","created":"2024-02-01","cited_by_count":11,"area":null},{"id":"2210.02199","title":"MTSMAE: Masked Autoencoders for Multivariate Time-Series Forecasting","created":"2022-10-04","cited_by_count":9,"area":null},{"id":"2407.14651","title":"Improving Representation of High-frequency Components for Medical Visual Foundation Models","created":"2024-07-19","cited_by_count":9,"area":null},{"id":"2509.17562","title":"Visual Instruction Pretraining for Domain-Specific Foundation Models","created":"2025-09-22","cited_by_count":9,"area":null},{"id":"2210.11404","title":"Self-Supervised Learning with Masked Image Modeling for Teeth Numbering, Detection of Dental Restorations, and Instance Segmentation in Dental Panoramic Radiographs","created":"2022-10-20","cited_by_count":8,"area":null},{"id":"2407.13036","title":"ColorMAE: Exploring data-independent masking strategies in Masked AutoEncoders","created":"2024-07-17","cited_by_count":8,"area":null},{"id":"2212.06593","title":"FastMIM: Expediting Masked Image Modeling Pre-training for Vision","created":"2022-12-13","cited_by_count":7,"area":null},{"id":"2301.00230","title":"Disjoint Masking with Joint Distillation for Efficient Masked Image Modeling","created":"2022-12-31","cited_by_count":6,"area":null},{"id":"2211.06012","title":"Masked Contrastive Representation Learning","created":"2022-11-11","cited_by_count":5,"area":null},{"id":"2301.01772","title":"Infomaxformer: Maximum Entropy Transformer for Long Time-Series Forecasting Problem","created":"2023-01-04","cited_by_count":5,"area":null},{"id":"2312.13714","title":"Bootstrap Masked Visual Modeling via Hard Patches Mining","created":"2023-12-21","cited_by_count":5,"area":null},{"id":"2412.13454","title":"Pre-training a Density-Aware Pose Transformer for Robust LiDAR-based 3D Human Pose Estimation","created":"2024-12-18","cited_by_count":5,"area":null},{"id":"2306.04715","title":"UniBoost: Unsupervised Unimodal Pre-training for Boosting Zero-shot Vision-Language Tasks","created":"2023-06-07","cited_by_count":4,"area":null},{"id":"2301.12058","title":"Aerial Image Object Detection With Vision Transformer Detector (ViTDet)","created":"2023-01-28","cited_by_count":3,"area":null},{"id":"2408.12814","title":"From Few to More: Scribble-based Medical Image Segmentation via Masked Context Modeling and Continuous Pseudo Labels","created":"2024-08-23","cited_by_count":3,"area":null},{"id":"2503.00782","title":"Wavelet-Driven Masked Image Modeling: A Path to Efficient Visual Representation","created":"2025-03-02","cited_by_count":3,"area":null},{"id":"2508.10794","title":"VasoMIM: Vascular Anatomy-Aware Masked Image Modeling for Vessel Segmentation","created":"2025-08-14","cited_by_count":3,"area":null},{"id":"2302.14256","title":"Remote Sensing Scene Classification with Masked Image Modeling (MIM)","created":"2023-02-28","cited_by_count":2,"area":null},{"id":"2305.16319","title":"Image as First-Order Norm+Linear Autoregression: Unveiling Mathematical Invariance","created":"2023-05-25","cited_by_count":2,"area":null},{"id":"2310.05108","title":"Enhancing Representations through Heterogeneous Self-Supervised Learning","created":"2023-10-08","cited_by_count":2,"area":null},{"id":"2312.04398","title":"Intelligent Anomaly Detection for Lane Rendering Using Transformer with Self-Supervised Pre-Training and Customized Fine-Tuning","created":"2023-12-07","cited_by_count":2,"area":null},{"id":"2211.01785","title":"Rethinking Hierarchies in Pre-trained Plain Vision Transformer","created":"2022-11-03","cited_by_count":1,"area":null},{"id":"2302.13699","title":"MPS-AMS: Masked Patches Selection and Adaptive Masking Strategy Based Self-Supervised Medical Image Segmentation","created":"2023-02-27","cited_by_count":1,"area":null},{"id":"2310.12976","title":"Exploring Invariance in Images through One-way Wave Equations","created":"2023-10-19","cited_by_count":1,"area":null},{"id":"2312.02194","title":"Local Masking Meets Progressive Freezing: Crafting Efficient Vision Transformers for Self-Supervised Learning","created":"2023-12-02","cited_by_count":1,"area":null},{"id":"2406.17450","title":"Pseudo Labelling for Enhanced Masked Autoencoders","created":"2024-06-25","cited_by_count":1,"area":null},{"id":"2308.08884","title":"SRMAE: Masked Image Modeling for Scale-Invariant Deep Representations","created":"2023-08-17","cited_by_count":0,"area":null},{"id":"2308.12673","title":"Masked Feature Modelling: Feature Masking for the Unsupervised Pre-training of a Graph Attention Network Block for Bottom-up Video Event Recognition","created":"2023-08-24","cited_by_count":0,"area":null},{"id":"2309.04312","title":"AMLP: Adjustable Masking Lesion Patches for Self-Supervised Medical Image Segmentation","created":"2023-09-08","cited_by_count":0,"area":null},{"id":"2311.07871","title":"Dual-channel Prototype Network for few-shot Classification of Pathological Images","created":"2023-11-14","cited_by_count":0,"area":null},{"id":"2311.17267","title":"E-ViLM: Efficient Video-Language Model via Masked Video Modeling with Semantic Vector-Quantized Tokenizer","created":"2023-11-28","cited_by_count":0,"area":null},{"id":"2409.02676","title":"Improved Single Camera BEV Perception Using Multi-Camera Training","created":"2024-09-04","cited_by_count":0,"area":null},{"id":"2508.11354","title":"FunduSegmenter: Leveraging the RETFound Foundation Model for Joint Optic Disc and Optic Cup Segmentation in Retinal Fundus Images","created":"2025-08-15","cited_by_count":0,"area":null},{"id":"2603.09955","title":"From Semantics to Pixels: Coarse-to-Fine Masked Autoencoders for Hierarchical Visual Understanding","created":"2026-03-10","cited_by_count":0,"area":null},{"id":"2607.23554","title":"Neonatal Hypoxic-ischaemic Encephalopathy Classification from the EEG and HRV Signals Using a Conformer based Masked Autoencoder","created":"2026-07-26","cited_by_count":0,"area":null},{"id":"2609.38278","title":"Masked Swingers: Harnessing Data Augmentation to Advance Autoencoders for Self-Supervised Learning","created":"2026-09-29","cited_by_count":0,"area":null}],"next_cursor":null}