{"total":22,"rows":[{"id":"2210.01055","title":"CLIP2Point: Transfer CLIP to Point Cloud Classification with Image-Depth Pre-training","created":"2022-10-03","cited_by_count":160,"area":null},{"id":"2306.09347","title":"Segment Any Point Cloud Sequences by Distilling Vision Foundation Models","created":"2023-06-15","cited_by_count":125,"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":"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":"2301.00157","title":"Ponder: Point Cloud Pre-training via Neural Rendering","created":"2022-12-31","cited_by_count":50,"area":null},{"id":"2301.05709","title":"Self-Supervised Image-to-Point Distillation via Semantically Tolerant Contrastive Loss","created":"2023-01-12","cited_by_count":35,"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":"2305.05026","title":"Self-supervised Pre-training with Masked Shape Prediction for 3D Scene Understanding","created":"2023-05-08","cited_by_count":13,"area":null},{"id":"2501.04005","title":"LargeAD: Large-Scale Cross-Sensor Data Pretraining for Autonomous Driving","created":"2025-01-07","cited_by_count":12,"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":"2406.10115","title":"Shelf-Supervised Cross-Modal Pre-Training for 3D Object Detection","created":"2024-06-14","cited_by_count":9,"area":null},{"id":"2403.08760","title":"MIM4D: Masked Modeling with Multi-View Video for Autonomous Driving Representation Learning","created":"2024-03-13","cited_by_count":8,"area":null},{"id":"2405.14271","title":"Fine-grained Image-to-LiDAR Contrastive Distillation with Visual Foundation Models","created":"2024-05-23","cited_by_count":5,"area":null},{"id":"2602.24181","title":"A Mixed Diet Makes DINO An Omnivorous Vision Encoder","created":"2026-02-27","cited_by_count":4,"area":null},{"id":"2307.15569","title":"Point Clouds Are Specialized Images: A Knowledge Transfer Approach for 3D Understanding","created":"2023-07-28","cited_by_count":3,"area":null},{"id":"2303.00086","title":"Applying Plain Transformers to Real-World Point Clouds","created":"2023-02-28","cited_by_count":2,"area":null},{"id":"2311.10887","title":"Point Cloud Self-supervised Learning via 3D to Multi-view Masked Learner","created":"2023-11-17","cited_by_count":2,"area":null},{"id":"2605.01759","title":"PointCSP: Cross-Sample Semantic Propagation and Stability Preservation in Self-Supervised Point Cloud Learning","created":"2026-05-03","cited_by_count":1,"area":null},{"id":"2306.04237","title":"Randomized 3D Scene Generation for Generalizable Self-Supervised Pre-Training","created":"2023-06-07","cited_by_count":0,"area":null},{"id":"2406.11283","title":"Enhancing Generalizability of Representation Learning for Data-Efficient 3D Scene Understanding","created":"2024-06-17","cited_by_count":0,"area":null},{"id":"2503.19947","title":"Vanishing Depth: Training Generalized Depth Adapters with Sinusoidal Depth Preprocessing for Pretrained RGB Encoders","created":"2025-03-25","cited_by_count":0,"area":null},{"id":"2601.07855","title":"RoAD Benchmark: How LiDAR Models Fail under Coupled Domain Shifts and Label Evolution","created":"2026-01-09","cited_by_count":0,"area":null}],"next_cursor":null}