{"total":230,"rows":[{"id":"2212.14532","title":"Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial Representation Learning","created":"2022-12-30","cited_by_count":308,"area":null},{"id":"2305.08275","title":"ULIP-2: Towards Scalable Multimodal Pre-training for 3D Understanding","created":"2023-05-14","cited_by_count":202,"area":null},{"id":"2309.00615","title":"Point-Bind & Point-LLM: Aligning Point Cloud with Multi-modality for 3D Understanding, Generation, and Instruction Following","created":"2023-09-01","cited_by_count":194,"area":null},{"id":"2211.11682","title":"PointCLIP V2: Prompting CLIP and GPT for Powerful 3D Open-world Learning","created":"2022-11-21","cited_by_count":187,"area":null},{"id":"2312.08168","title":"Chat-Scene: Bridging 3D Scene and Large Language Models with Object Identifiers","created":"2023-12-13","cited_by_count":175,"area":null},{"id":"2302.02318","title":"Contrast with Reconstruct: Contrastive 3D Representation Learning Guided by Generative Pretraining","created":"2023-02-05","cited_by_count":164,"area":null},{"id":"2303.02151","title":"Prompt, Generate, then Cache: Cascade of Foundation Models makes Strong Few-shot Learners","created":"2023-03-03","cited_by_count":152,"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":"2308.08769","title":"Chat-3D: Data-efficiently Tuning Large Language Model for Universal Dialogue of 3D Scenes","created":"2023-08-17","cited_by_count":129,"area":null},{"id":"2208.02797","title":"Vision-Centric BEV Perception: A Survey","created":"2022-08-04","cited_by_count":126,"area":null},{"id":"2304.09854","title":"Transformer-Based Visual Segmentation: A Survey","created":"2023-04-19","cited_by_count":124,"area":null},{"id":"2305.11487","title":"PointGPT: Auto-regressively Generative Pre-training from Point Clouds","created":"2023-05-19","cited_by_count":115,"area":null},{"id":"2304.06906","title":"Swin3D: A Pretrained Transformer Backbone for 3D Indoor Scene Understanding","created":"2023-04-14","cited_by_count":113,"area":null},{"id":"2503.16429","title":"Sonata: Self-Supervised Learning of Reliable Point Representations","created":"2025-03-20","cited_by_count":110,"area":null},{"id":"2209.14169","title":"CALIP: Zero-Shot Enhancement of CLIP with Parameter-free Attention","created":"2022-09-28","cited_by_count":103,"area":null},{"id":"2303.04748","title":"CLIP-FO3D: Learning Free Open-world 3D Scene Representations from 2D Dense CLIP","created":"2023-03-08","cited_by_count":89,"area":null},{"id":"2403.05419","title":"Rethinking Transformers Pre-training for Multi-Spectral Satellite Imagery","created":"2024-03-08","cited_by_count":83,"area":null},{"id":"2208.02812","title":"P2P: Tuning Pre-trained Image Models for Point Cloud Analysis with Point-to-Pixel Prompting","created":"2022-08-04","cited_by_count":74,"area":null},{"id":"2310.08370","title":"UniPAD: A Universal Pre-training Paradigm for Autonomous Driving","created":"2023-10-12","cited_by_count":73,"area":null},{"id":"2303.16894","title":"ViewRefer: Grasp the Multi-view Knowledge for 3D Visual Grounding with GPT and Prototype Guidance","created":"2023-03-29","cited_by_count":70,"area":null},{"id":"2303.12417","title":"CLIP$^2$: Contrastive Language-Image-Point Pretraining from Real-World Point Cloud Data","created":"2023-03-22","cited_by_count":69,"area":null},{"id":"2304.07221","title":"Instance-aware Dynamic Prompt Tuning for Pre-trained Point Cloud Models","created":"2023-04-14","cited_by_count":68,"area":null},{"id":"2206.09900","title":"Occupancy-MAE: Self-supervised Pre-training Large-scale LiDAR Point Clouds with Masked Occupancy Autoencoders","created":"2022-06-20","cited_by_count":58,"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":"2212.03010","title":"GD-MAE: Generative Decoder for MAE Pre-training on LiDAR Point Clouds","created":"2022-12-06","cited_by_count":57,"area":null},{"id":"2310.08586","title":"PonderV2: Pave the Way for 3D Foundation Model with A Universal Pre-training Paradigm","created":"2023-10-12","cited_by_count":56,"area":null},{"id":"2303.08129","title":"PiMAE: Point Cloud and Image Interactive Masked Autoencoders for 3D Object Detection","created":"2023-03-14","cited_by_count":53,"area":null},{"id":"2403.01439","title":"Dynamic Adapter Meets Prompt Tuning: Parameter-Efficient Transfer Learning for Point Cloud Analysis","created":"2024-03-03","cited_by_count":53,"area":null},{"id":"2302.14007","title":"Joint-MAE: 2D-3D Joint Masked Autoencoders for 3D Point Cloud Pre-training","created":"2023-02-27","cited_by_count":52,"area":null},{"id":"2301.00157","title":"Ponder: Point Cloud Pre-training via Neural Rendering","created":"2022-12-31","cited_by_count":50,"area":null},{"id":"2409.03757","title":"Lexicon3D: Probing Visual Foundation Models for Complex 3D Scene Understanding","created":"2024-09-05","cited_by_count":49,"area":null},{"id":"2402.02500","title":"Point Cloud Matters: Rethinking the Impact of Different Observation Spaces on Robot Learning","created":"2024-02-04","cited_by_count":45,"area":null},{"id":"2310.17504","title":"Three Pillars improving Vision Foundation Model Distillation for Lidar","created":"2023-10-26","cited_by_count":44,"area":null},{"id":"2410.08114","title":"Parameter-Efficient Fine-Tuning in Spectral Domain for Point Cloud Learning","created":"2024-10-10","cited_by_count":43,"area":null},{"id":"2303.06697","title":"Traj-MAE: Masked Autoencoders for Trajectory Prediction","created":"2023-03-12","cited_by_count":42,"area":null},{"id":"2310.03059","title":"Point-PEFT: Parameter-Efficient Fine-Tuning for 3D Pre-trained Models","created":"2023-10-04","cited_by_count":42,"area":null},{"id":"2312.10726","title":"Towards Compact 3D Representations via Point Feature Enhancement Masked Autoencoders","created":"2023-12-17","cited_by_count":42,"area":null},{"id":"2306.08659","title":"Explore In-Context Learning for 3D Point Cloud Understanding","created":"2023-06-14","cited_by_count":40,"area":null},{"id":"2207.00531","title":"Masked Autoencoder for Self-Supervised Pre-training on Lidar Point Clouds","created":"2022-07-01","cited_by_count":39,"area":null},{"id":"2303.08134","title":"Parameter is Not All You Need: Starting from Non-Parametric Networks for 3D Point Cloud Analysis","created":"2023-03-14","cited_by_count":34,"area":null},{"id":"2207.01545","title":"Masked Autoencoders in 3D Point Cloud Representation Learning","created":"2022-07-04","cited_by_count":30,"area":null},{"id":"2404.16432","title":"Point-JEPA: A Joint Embedding Predictive Architecture for Self-Supervised Learning on Point Cloud","created":"2024-04-25","cited_by_count":30,"area":null},{"id":"2212.03814","title":"iQuery: Instruments as Queries for Audio-Visual Sound Separation","created":"2022-12-07","cited_by_count":29,"area":null},{"id":"2303.16570","title":"Point2Vec for Self-Supervised Representation Learning on Point Clouds","created":"2023-03-29","cited_by_count":28,"area":null},{"id":"2402.18490","title":"TAMM: TriAdapter Multi-Modal Learning for 3D Shape Understanding","created":"2024-02-28","cited_by_count":27,"area":null},{"id":"2303.13510","title":"MV-JAR: Masked Voxel Jigsaw and Reconstruction for LiDAR-Based Self-Supervised Pre-Training","created":"2023-03-23","cited_by_count":26,"area":null},{"id":"2307.14971","title":"Take-A-Photo: 3D-to-2D Generative Pre-training of Point Cloud Models","created":"2023-07-27","cited_by_count":25,"area":null},{"id":"2404.13506","title":"Parameter Efficient Fine Tuning: A Comprehensive Analysis Across Applications","created":"2024-04-21","cited_by_count":25,"area":null},{"id":"2307.11914","title":"Building3D: An Urban-Scale Dataset and Benchmarks for Learning Roof Structures from Point Clouds","created":"2023-07-21","cited_by_count":24,"area":null},{"id":"2310.17281","title":"BEVContrast: Self-Supervision in BEV Space for Automotive Lidar Point Clouds","created":"2023-10-26","cited_by_count":24,"area":null},{"id":"2408.08753","title":"PCP-MAE: Learning to Predict Centers for Point Masked Autoencoders","created":"2024-08-16","cited_by_count":24,"area":null},{"id":"2404.07989","title":"Any2Point: Empowering Any-modality Large Models for Efficient 3D Understanding","created":"2024-04-11","cited_by_count":23,"area":null},{"id":"2504.14151","title":"Locate 3D: Real-World Object Localization via Self-Supervised Learning in 3D","created":"2025-04-19","cited_by_count":23,"area":null},{"id":"2212.05758","title":"BEV-MAE: Bird's Eye View Masked Autoencoders for Point Cloud Pre-training in Autonomous Driving Scenarios","created":"2022-12-12","cited_by_count":21,"area":null},{"id":"2305.04691","title":"Self-supervised Learning for Pre-Training 3D Point Clouds: A Survey","created":"2023-05-08","cited_by_count":21,"area":null},{"id":"2405.15214","title":"PointRWKV: Efficient RWKV-Like Model for Hierarchical Point Cloud Learning","created":"2024-05-24","cited_by_count":21,"area":null},{"id":"2408.10906","title":"ShapeSplat: A Large-scale Dataset of Gaussian Splats and Their Self-Supervised Pretraining","created":"2024-08-20","cited_by_count":21,"area":null},{"id":"2603.03283","title":"Utonia: Toward One Encoder for All Point Clouds","created":"2026-03-03","cited_by_count":21,"area":null},{"id":"2212.07207","title":"MAELi: Masked Autoencoder for Large-Scale LiDAR Point Clouds","created":"2022-12-14","cited_by_count":20,"area":null},{"id":"2404.01300","title":"NeRF-MAE: Masked AutoEncoders for Self-Supervised 3D Representation Learning for Neural Radiance Fields","created":"2024-04-01","cited_by_count":20,"area":null},{"id":"2407.15837","title":"Towards Latent Masked Image Modeling for Self-Supervised Visual Representation Learning","created":"2024-07-22","cited_by_count":20,"area":null},{"id":"2404.15580","title":"MiM: Mask in Mask Self-Supervised Pre-Training for 3D Medical Image Analysis","created":"2024-04-24","cited_by_count":19,"area":null},{"id":"2510.25785","title":"HiMAE: Hierarchical Masked Autoencoders Discover Resolution-Specific Structure in Wearable Time Series","created":"2025-10-28","cited_by_count":19,"area":null},{"id":"2404.04050","title":"No Time to Train: Empowering Non-Parametric Networks for Few-shot 3D Scene Segmentation","created":"2024-04-05","cited_by_count":18,"area":null},{"id":"2412.08641","title":"3D Mesh Editing using Masked LRMs","created":"2024-12-11","cited_by_count":18,"area":null},{"id":"2602.23069","title":"Align then Adapt: Rethinking Parameter-Efficient Transfer Learning in 4D Perception","created":"2026-02-26","cited_by_count":18,"area":null},{"id":"2303.11325","title":"GeoMIM: Towards Better 3D Knowledge Transfer via Masked Image Modeling for Multi-view 3D Understanding","created":"2023-03-20","cited_by_count":17,"area":null},{"id":"2311.18113","title":"Back to 3D: Few-Shot 3D Keypoint Detection with Back-Projected 2D Features","created":"2023-11-29","cited_by_count":17,"area":null},{"id":"2306.10474","title":"A Universal Semantic-Geometric Representation for Robotic Manipulation","created":"2023-06-18","cited_by_count":16,"area":null},{"id":"2402.15823","title":"Parameter-efficient Prompt Learning for 3D Point Cloud Understanding","created":"2024-02-24","cited_by_count":16,"area":null},{"id":"2407.05862","title":"Bringing Masked Autoencoders Explicit Contrastive Properties for Point Cloud Self-Supervised Learning","created":"2024-07-08","cited_by_count":16,"area":null},{"id":"2207.03111","title":"Masked Surfel Prediction for Self-Supervised Point Cloud Learning","created":"2022-07-07","cited_by_count":15,"area":null},{"id":"2312.01758","title":"CILF-CIAE: CLIP-driven Image-Language Fusion for Correcting Inverse Age Estimation","created":"2023-12-04","cited_by_count":15,"area":null},{"id":"2312.09738","title":"3DAxiesPrompts: Unleashing the 3D Spatial Task Capabilities of GPT-4V","created":"2023-12-15","cited_by_count":15,"area":null},{"id":"2408.11567","title":"Positional Prompt Tuning for Efficient 3D Representation Learning","created":"2024-08-21","cited_by_count":15,"area":null},{"id":"2409.00353","title":"RI-MAE: Rotation-Invariant Masked AutoEncoders for Self-Supervised Point Cloud Representation Learning","created":"2024-08-31","cited_by_count":15,"area":null},{"id":"2305.19623","title":"Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color Contrast","created":"2023-05-31","cited_by_count":14,"area":null},{"id":"2307.16605","title":"VPP: Efficient Conditional 3D Generation via Voxel-Point Progressive Representation","created":"2023-07-28","cited_by_count":14,"area":null},{"id":"2409.15803","title":"3D-JEPA: A Joint Embedding Predictive Architecture for 3D Self-Supervised Representation Learning","created":"2024-09-24","cited_by_count":14,"area":null},{"id":"2504.16023","title":"PointLoRA: Low-Rank Adaptation with Token Selection for Point Cloud Learning","created":"2025-04-22","cited_by_count":14,"area":null},{"id":"2304.06911","title":"3D Feature Prediction for Masked-AutoEncoder-Based Point Cloud Pretraining","created":"2023-04-14","cited_by_count":13,"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":"2406.03051","title":"Adapter-X: A Novel General Parameter-Efficient Fine-Tuning Framework for Vision","created":"2024-06-05","cited_by_count":13,"area":null},{"id":"2505.04119","title":"GAPrompt: Geometry-Aware Point Cloud Prompt for 3D Vision Model","created":"2025-05-07","cited_by_count":13,"area":null},{"id":"2212.09948","title":"MM-3DScene: 3D Scene Understanding by Customizing Masked Modeling with Informative-Preserved Reconstruction and Self-Distilled Consistency","created":"2022-12-20","cited_by_count":12,"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":"2310.20293","title":"Annotator: A Generic Active Learning Baseline for LiDAR Semantic Segmentation","created":"2023-10-31","cited_by_count":11,"area":null},{"id":"2311.18402","title":"MV-CLIP: Multi-View CLIP for Zero-shot 3D Shape Recognition","created":"2023-11-30","cited_by_count":11,"area":null},{"id":"2312.10217","title":"T-MAE: Temporal Masked Autoencoders for Point Cloud Representation Learning","created":"2023-12-15","cited_by_count":11,"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":"2408.11241","title":"CooPre: Cooperative Pretraining for V2X Cooperative Perception","created":"2024-08-20","cited_by_count":11,"area":null},{"id":"2211.06841","title":"Point-DAE: Denoising Autoencoders for Self-supervised Point Cloud Learning","created":"2022-11-13","cited_by_count":9,"area":null},{"id":"2310.16861","title":"General Point Model with Autoencoding and Autoregressive","created":"2023-10-25","cited_by_count":9,"area":null},{"id":"2403.00416","title":"Data-efficient Event Camera Pre-training via Disentangled Masked Modeling","created":"2024-03-01","cited_by_count":9,"area":null},{"id":"2410.19872","title":"Radar and Camera Fusion for Object Detection and Tracking: A Comprehensive Survey","created":"2024-10-24","cited_by_count":9,"area":null},{"id":"2210.11470","title":"i-MAE: Are Latent Representations in Masked Autoencoders Linearly Separable?","created":"2022-10-20","cited_by_count":8,"area":null},{"id":"2309.08728","title":"SculptBot: Pre-Trained Models for 3D Deformable Object Manipulation","created":"2023-09-15","cited_by_count":8,"area":null},{"id":"2403.10760","title":"CORN: Contact-based Object Representation for Nonprehensile Manipulation of General Unseen Objects","created":"2024-03-16","cited_by_count":8,"area":null},{"id":"2403.15835","title":"Once for Both: Single Stage of Importance and Sparsity Search for Vision Transformer Compression","created":"2024-03-23","cited_by_count":8,"area":null},{"id":"2407.10200","title":"Shape2Scene: 3D Scene Representation Learning Through Pre-training on Shape Data","created":"2024-07-14","cited_by_count":8,"area":null}],"next_cursor":"100"}