{"total":62,"rows":[{"id":"2211.07636","title":"EVA: Exploring the Limits of Masked Visual Representation Learning at Scale","created":"2022-11-14","cited_by_count":691,"area":null},{"id":"2303.11331","title":"EVA-02: A Visual Representation for Neon Genesis","created":"2023-03-20","cited_by_count":381,"area":null},{"id":"2212.00794","title":"Scaling Language-Image Pre-training via Masking","created":"2022-12-01","cited_by_count":317,"area":null},{"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":"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":"2303.16058","title":"Unmasked Teacher: Towards Training-Efficient Video Foundation Models","created":"2023-03-28","cited_by_count":199,"area":null},{"id":"2312.00863","title":"EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything","created":"2023-12-01","cited_by_count":188,"area":null},{"id":"2212.06785","title":"Learning 3D Representations from 2D Pre-trained Models via Image-to-Point Masked Autoencoders","created":"2022-12-13","cited_by_count":144,"area":null},{"id":"2304.05919","title":"Hard Patches Mining for Masked Image Modeling","created":"2023-04-12","cited_by_count":57,"area":null},{"id":"2211.09120","title":"AdaMAE: Adaptive Masking for Efficient Spatiotemporal Learning with Masked Autoencoders","created":"2022-11-16","cited_by_count":43,"area":null},{"id":"2305.13689","title":"Know Your Self-supervised Learning: A Survey on Image-based Generative and Discriminative Training","created":"2023-05-23","cited_by_count":39,"area":null},{"id":"2211.16327","title":"On the Power of Foundation Models","created":"2022-11-29","cited_by_count":37,"area":null},{"id":"2210.10615","title":"A Unified View of Masked Image Modeling","created":"2022-10-19","cited_by_count":36,"area":null},{"id":"2211.09807","title":"Towards All-in-one Pre-training via Maximizing Multi-modal Mutual Information","created":"2022-11-17","cited_by_count":31,"area":null},{"id":"2309.00775","title":"Contrastive Feature Masking Open-Vocabulary Vision Transformer","created":"2023-09-02","cited_by_count":31,"area":null},{"id":"2211.08887","title":"Stare at What You See: Masked Image Modeling without Reconstruction","created":"2022-11-16","cited_by_count":30,"area":null},{"id":"2312.12480","title":"Continual-MAE: Adaptive Distribution Masked Autoencoders for Continual Test-Time Adaptation","created":"2023-12-19","cited_by_count":30,"area":null},{"id":"2303.02416","title":"PixMIM: Rethinking Pixel Reconstruction in Masked Image Modeling","created":"2023-03-04","cited_by_count":28,"area":null},{"id":"2211.09799","title":"CAE v2: Context Autoencoder with CLIP Target","created":"2022-11-17","cited_by_count":25,"area":null},{"id":"2307.12545","title":"Towards Video Anomaly Retrieval from Video Anomaly Detection: New Benchmarks and Model","created":"2023-07-24","cited_by_count":25,"area":null},{"id":"2301.01296","title":"TinyMIM: An Empirical Study of Distilling MIM Pre-trained Models","created":"2023-01-03","cited_by_count":24,"area":null},{"id":"2308.00261","title":"Improving Pixel-based MIM by Reducing Wasted Modeling Capability","created":"2023-08-01","cited_by_count":24,"area":null},{"id":"2412.12032","title":"FSFM: A Generalizable Face Security Foundation Model via Self-Supervised Facial Representation Learning","created":"2024-12-16","cited_by_count":23,"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":"2407.12210","title":"A Closer Look at Benchmarking Self-Supervised Pre-training with Image Classification","created":"2024-07-16","cited_by_count":19,"area":null},{"id":"2504.09209","title":"EchoMask: Speech-Queried Attention-based Mask Modeling for Holistic Co-Speech Motion Generation","created":"2025-04-12","cited_by_count":17,"area":null},{"id":"2303.08817","title":"DeepMIM: Deep Supervision for Masked Image Modeling","created":"2023-03-15","cited_by_count":16,"area":null},{"id":"2312.02147","title":"Rejuvenating image-GPT as Strong Visual Representation Learners","created":"2023-12-04","cited_by_count":16,"area":null},{"id":"2404.08327","title":"Salience-Based Adaptive Masking: Revisiting Token Dynamics for Enhanced Pre-training","created":"2024-04-12","cited_by_count":14,"area":null},{"id":"2410.12957","title":"MuVi: Video-to-Music Generation with Semantic Alignment and Rhythmic Synchronization","created":"2024-10-16","cited_by_count":14,"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":"2301.06958","title":"RILS: Masked Visual Reconstruction in Language Semantic Space","created":"2023-01-17","cited_by_count":10,"area":null},{"id":"2404.08330","title":"Emerging Property of Masked Token for Effective Pre-training","created":"2024-04-12","cited_by_count":10,"area":null},{"id":"2307.09361","title":"MOCA: Self-supervised Representation Learning by Predicting Masked Online Codebook Assignments","created":"2023-07-18","cited_by_count":9,"area":null},{"id":"2407.16541","title":"QPT V2: Masked Image Modeling Advances Visual Scoring","created":"2024-07-23","cited_by_count":8,"area":null},{"id":"2507.16318","title":"M-SpecGene: Generalized Foundation Model for RGBT Multispectral Vision","created":"2025-07-22","cited_by_count":8,"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":"2305.07910","title":"Mask to reconstruct: Cooperative Semantics Completion for Video-text Retrieval","created":"2023-05-13","cited_by_count":5,"area":null},{"id":"2305.15248","title":"Delving Deeper into Data Scaling in Masked Image Modeling","created":"2023-05-24","cited_by_count":5,"area":null},{"id":"2312.08192","title":"PAD: Self-Supervised Pre-Training with Patchwise-Scale Adapter for Infrared Images","created":"2023-12-13","cited_by_count":5,"area":null},{"id":"2404.12210","title":"An Experimental Study on Exploring Strong Lightweight Vision Transformers via Masked Image Modeling Pre-Training","created":"2024-04-18","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":"2306.07346","title":"Learning to Mask and Permute Visual Tokens for Vision Transformer Pre-Training","created":"2023-06-12","cited_by_count":3,"area":null},{"id":"2306.11339","title":"Masking meets Supervision: A Strong Learning Alliance","created":"2023-06-20","cited_by_count":3,"area":null},{"id":"2502.02257","title":"UNIP: Rethinking Pre-trained Attention Patterns for Infrared Semantic Segmentation","created":"2025-02-04","cited_by_count":3,"area":null},{"id":"2506.18463","title":"DIP: Unsupervised Dense In-Context Post-training of Visual Representations","created":"2025-06-23","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":"2311.03149","title":"Asymmetric Masked Distillation for Pre-Training Small Foundation Models","created":"2023-11-06","cited_by_count":2,"area":null},{"id":"2312.10457","title":"Semantic-Aware Autoregressive Image Modeling for Visual Representation Learning","created":"2023-12-16","cited_by_count":2,"area":null},{"id":"2406.10673","title":"SemanticMIM: Marring Masked Image Modeling with Semantics Compression for General Visual Representation","created":"2024-06-15","cited_by_count":2,"area":null},{"id":"2407.11537","title":"AEMIM: Adversarial Examples Meet Masked Image Modeling","created":"2024-07-16","cited_by_count":2,"area":null},{"id":"2410.07442","title":"Self-Supervised Learning for Real-World Object Detection: a Survey","created":"2024-10-09","cited_by_count":2,"area":null},{"id":"2508.05507","title":"Revealing Latent Information: A Physics-inspired Self-supervised Pre-training Framework for Noisy and Sparse Events","created":"2025-08-07","cited_by_count":2,"area":null},{"id":"2603.22953","title":"Cluster-Wise Spatio-Temporal Masking for Efficient Video-Language Pretraining","created":"2026-03-24","cited_by_count":2,"area":null},{"id":"2603.29655","title":"Not All Frames Are Equal: Complexity-Aware Masked Motion Generation via Motion Spectral Descriptors","created":"2026-03-31","cited_by_count":2,"area":null},{"id":"2506.19022","title":"Orthogonal Projection Subspace to Aggregate Online Prior-knowledge for Continual Test-time Adaptation","created":"2025-06-23","cited_by_count":1,"area":null},{"id":"2405.05745","title":"Efficient Pretraining Model based on Multi-Scale Local Visual Field Feature Reconstruction for PCB CT Image Element Segmentation","created":"2024-05-09","cited_by_count":0,"area":null},{"id":"2509.15642","title":"UNIV: Unified Foundation Model for Infrared and Visible Modalities","created":"2025-09-19","cited_by_count":0,"area":null},{"id":"2512.04511","title":"DuGI-MAE: Improving Infrared Mask Autoencoders via Dual-Domain Guidance","created":"2025-12-04","cited_by_count":0,"area":null},{"id":"2603.29009","title":"MEDiC: Multi-objective Exploration of Distillation from CLIP","created":"2026-03-30","cited_by_count":0,"area":null},{"id":"2608.07984","title":"AgriField-40K: Adapting Vision Models to Agriculture With Efficient Continual Pretraining","created":"2026-08-08","cited_by_count":0,"area":null}],"next_cursor":null}