{"total":47,"rows":[{"id":"2312.10035","title":"Point Transformer V3: Simpler, Faster, Stronger","created":"2023-12-15","cited_by_count":589,"area":null},{"id":"2303.17597","title":"Robo3D: Towards Robust and Reliable 3D Perception against Corruptions","created":"2023-03-30","cited_by_count":129,"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":"2308.09718","title":"Towards Large-scale 3D Representation Learning with Multi-dataset Point Prompt Training","created":"2023-08-18","cited_by_count":86,"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":"2309.05573","title":"UniSeg: A Unified Multi-Modal LiDAR Segmentation Network and the OpenPCSeg Codebase","created":"2023-09-11","cited_by_count":57,"area":null},{"id":"2312.04484","title":"FRNet: Frustum-Range Networks for Scalable LiDAR Segmentation","created":"2023-12-07","cited_by_count":50,"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":"2312.02158","title":"PaSCo: Urban 3D Panoptic Scene Completion with Uncertainty Awareness","created":"2023-12-04","cited_by_count":42,"area":null},{"id":"2405.17426","title":"Benchmarking and Improving Bird's Eye View Perception Robustness in Autonomous Driving","created":"2024-05-27","cited_by_count":41,"area":null},{"id":"2403.17009","title":"Is Your LiDAR Placement Optimized for 3D Scene Understanding?","created":"2024-03-25","cited_by_count":26,"area":null},{"id":"2405.01538","title":"Multi-Space Alignments Towards Universal LiDAR Segmentation","created":"2024-05-02","cited_by_count":25,"area":null},{"id":"2403.11496","title":"MCD: Diverse Large-Scale Multi-Campus Dataset for Robot Perception","created":"2024-03-18","cited_by_count":16,"area":null},{"id":"2407.02286","title":"Rethinking Data Augmentation for Robust LiDAR Semantic Segmentation in Adverse Weather","created":"2024-07-02","cited_by_count":14,"area":null},{"id":"2407.11569","title":"SFPNet: Sparse Focal Point Network for Semantic Segmentation on General LiDAR Point Clouds","created":"2024-07-16","cited_by_count":13,"area":null},{"id":"2405.14870","title":"An Empirical Study of Training State-of-the-Art LiDAR Segmentation Models","created":"2024-05-23","cited_by_count":12,"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":"2503.00803","title":"HiMo: High-Speed Objects Motion Compensation in Point Clouds","created":"2025-03-02","cited_by_count":12,"area":null},{"id":"2511.01755","title":"3EED: Ground Everything Everywhere in 3D","created":"2025-11-03","cited_by_count":12,"area":null},{"id":"2403.17010","title":"Calib3D: Calibrating Model Preferences for Reliable 3D Scene Understanding","created":"2024-03-25","cited_by_count":11,"area":null},{"id":"2502.03901","title":"LeAP: Consistent multi-domain 3D labeling using Foundation Models","created":"2025-02-06","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":"2505.24634","title":"NUC-Net: Non-uniform Cylindrical Partition Network for Efficient LiDAR Semantic Segmentation","created":"2025-05-30","cited_by_count":5,"area":null},{"id":"2410.10510","title":"Exploiting Local Features and Range Images for Small Data Real-Time Point Cloud Semantic Segmentation","created":"2024-10-14","cited_by_count":4,"area":null},{"id":"2503.23980","title":"SALT: A Flexible Semi-Automatic Labeling Tool for General LiDAR Point Clouds with Cross-Scene Adaptability and 4D Consistency","created":"2025-03-31","cited_by_count":4,"area":null},{"id":"2502.09274","title":"FLARES: Fast and Accurate LiDAR Multi-Range Semantic Segmentation","created":"2025-02-13","cited_by_count":3,"area":null},{"id":"2504.21602","title":"Real Time Semantic Segmentation of High Resolution Automotive LiDAR Scans","created":"2025-04-30","cited_by_count":2,"area":null},{"id":"2511.17455","title":"Improving Multimodal Distillation for 3D Semantic Segmentation under Domain Shift","created":"2025-11-21","cited_by_count":2,"area":null},{"id":"2606.03992","title":"Exploring Easy Boosts for Lidar Semantic Scene Completion","created":"2026-06-02","cited_by_count":2,"area":null},{"id":"2410.08365","title":"Are We Ready for Real-Time LiDAR Semantic Segmentation in Autonomous Driving?","created":"2024-10-10","cited_by_count":1,"area":null},{"id":"2411.11935","title":"Calibrated and Efficient Sampling-Free Confidence Estimation for LiDAR Scene Semantic Segmentation","created":"2024-11-18","cited_by_count":1,"area":null},{"id":"2503.13203","title":"Is clustering enough for LiDAR instance segmentation? A state-of-the-art training-free baseline","created":"2025-03-17","cited_by_count":1,"area":null},{"id":"2510.06876","title":"HARP-NeXt: High-Speed and Accurate Range-Point Fusion Network for 3D LiDAR Semantic Segmentation","created":"2025-10-08","cited_by_count":1,"area":null},{"id":"2605.17135","title":"Collaborative Learning for Semi-Supervised LiDAR Semantic Segmentation","created":"2026-05-16","cited_by_count":1,"area":null},{"id":"2607.10762","title":"TOLiD: Bridging the Architecture Gap in Vision Foundation Model to LiDAR Pretraining via Token Lifting for Distillation","created":"2026-07-12","cited_by_count":1,"area":null},{"id":"2405.10046","title":"A Preprocessing and Postprocessing Voxel-based Method for LiDAR Semantic Segmentation Improvement in Long Distance","created":"2024-05-16","cited_by_count":0,"area":null},{"id":"2407.15797","title":"MILAN: Milli-Annotations for Lidar Semantic Segmentation","created":"2024-07-22","cited_by_count":0,"area":null},{"id":"2502.12860","title":"An Experimental Study of SOTA LiDAR Segmentation Models","created":"2025-02-18","cited_by_count":0,"area":null},{"id":"2503.14955","title":"Depth-Aware Range Image-Based Model for Point Cloud Segmentation","created":"2025-03-19","cited_by_count":0,"area":null},{"id":"2510.10471","title":"DAGLFNet: Deep Feature Attention Guided Global and Local Feature Fusion for Pseudo-Image Point Cloud Segmentation","created":"2025-10-12","cited_by_count":0,"area":null},{"id":"2602.12524","title":"LiDAR-Anchored Collaborative Distillation for Robust 2D Representations","created":"2026-02-13","cited_by_count":0,"area":null},{"id":"2603.01074","title":"Adaptive Augmentation-Aware Latent Learning for Robust LiDAR Semantic Segmentation","created":"2026-03-01","cited_by_count":0,"area":null},{"id":"2603.04099","title":"Efficient Point Cloud Processing with High-Dimensional Positional Encoding and Non-Local MLPs","created":"2026-03-04","cited_by_count":0,"area":null},{"id":"2604.01361","title":"IGLOSS: Image Generation for Lidar Open-vocabulary Semantic Segmentation","created":"2026-04-01","cited_by_count":0,"area":null},{"id":"2604.12935","title":"Task Alignment: A Simple Proxy for Practical Model Merging Across Diverse Vision Tasks","created":"2026-04-14","cited_by_count":0,"area":null},{"id":"2604.23604","title":"Learning to Identify Out-of-Distribution Objects for 3D LiDAR Anomaly Segmentation","created":"2026-04-26","cited_by_count":0,"area":null},{"id":"2605.31177","title":"Vanilla ViT for Automotive Point Cloud Semantic Segmentation","created":"2026-05-29","cited_by_count":0,"area":null}],"next_cursor":null}