{"total":33,"rows":[{"id":"2204.12463","title":"Focal Sparse Convolutional Networks for 3D Object Detection","created":"2022-04-26","cited_by_count":142,"area":null},{"id":"2203.03311","title":"Comprehensive Review of Deep Learning-Based 3D Point Cloud Completion Processing and Analysis","created":"2022-03-07","cited_by_count":44,"area":null},{"id":"2204.00325","title":"CAT-Det: Contrastively Augmented Transformer for Multi-modal 3D Object Detection","created":"2022-04-01","cited_by_count":32,"area":null},{"id":"2303.12621","title":"OcTr: Octree-based Transformer for 3D Object Detection","created":"2023-03-22","cited_by_count":32,"area":null},{"id":"2307.11477","title":"SA-BEV: Generating Semantic-Aware Bird's-Eye-View Feature for Multi-view 3D Object Detection","created":"2023-07-21","cited_by_count":30,"area":null},{"id":"2405.02595","title":"Vision-based 3D occupancy prediction in autonomous driving: a review and outlook","created":"2024-05-04","cited_by_count":29,"area":null},{"id":"2503.03430","title":"CoSDH: Communication-Efficient Collaborative Perception via Supply-Demand Awareness and Intermediate-Late Hybridization","created":"2025-03-05","cited_by_count":28,"area":null},{"id":"2211.13067","title":"Sparse2Dense: Learning to Densify 3D Features for 3D Object Detection","created":"2022-11-23","cited_by_count":14,"area":null},{"id":"2307.12637","title":"PG-RCNN: Semantic Surface Point Generation for 3D Object Detection","created":"2023-07-24","cited_by_count":12,"area":null},{"id":"2401.00912","title":"ScatterFormer: Efficient Voxel Transformer with Scattered Linear Attention","created":"2024-01-01","cited_by_count":11,"area":null},{"id":"2111.11976","title":"KTNet: Knowledge Transfer for Unpaired 3D Shape Completion","created":"2021-11-23","cited_by_count":9,"area":null},{"id":"2407.17877","title":"Advancing 3D Point Cloud Understanding through Deep Transfer Learning: A Comprehensive Survey","created":"2024-07-25","cited_by_count":9,"area":null},{"id":"2307.00347","title":"Spatial-Temporal Graph Enhanced DETR Towards Multi-Frame 3D Object Detection","created":"2023-07-01","cited_by_count":8,"area":null},{"id":"2211.08248","title":"3D Cascade RCNN: High Quality Object Detection in Point Clouds","created":"2022-11-15","cited_by_count":7,"area":null},{"id":"2406.10907","title":"SparseDet: A Simple and Effective Framework for Fully Sparse LiDAR-based 3D Object Detection","created":"2024-06-16","cited_by_count":7,"area":null},{"id":"2207.01030","title":"Boosting Single-Frame 3D Object Detection by Simulating Multi-Frame Point Clouds","created":"2022-07-03","cited_by_count":6,"area":null},{"id":"2406.19362","title":"STAL3D: Unsupervised Domain Adaptation for 3D Object Detection via Collaborating Self-Training and Adversarial Learning","created":"2024-06-27","cited_by_count":6,"area":null},{"id":"2602.20653","title":"SD4R: Sparse-to-Dense Learning for 3D Object Detection with 4D Radar","created":"2026-02-24","cited_by_count":4,"area":null},{"id":"2208.13414","title":"PV-RCNN++: Semantical Point-Voxel Feature Interaction for 3D Object Detection","created":"2022-08-29","cited_by_count":3,"area":null},{"id":"2403.02818","title":"Are Dense Labels Always Necessary for 3D Object Detection from Point Cloud?","created":"2024-03-05","cited_by_count":2,"area":null},{"id":"2408.05674","title":"PS-TTL: Prototype-based Soft-labels and Test-Time Learning for Few-shot Object Detection","created":"2024-08-11","cited_by_count":2,"area":null},{"id":"2209.04362","title":"EDeNN: Event Decay Neural Networks for low latency vision","created":"2022-09-09","cited_by_count":1,"area":null},{"id":"2310.17842","title":"What You See Is What You Detect: Towards better Object Densification in 3D detection","created":"2023-10-27","cited_by_count":1,"area":null},{"id":"2312.12743","title":"PointeNet: A Lightweight Framework for Effective and Efficient Point Cloud Analysis","created":"2023-12-20","cited_by_count":1,"area":null},{"id":"2404.03572","title":"Terrain Point Cloud Inpainting via Signal Decomposition","created":"2024-04-04","cited_by_count":1,"area":null},{"id":"2408.14600","title":"PVAFN: Point-Voxel Attention Fusion Network with Multi-Pooling Enhancing for 3D Object Detection","created":"2024-08-26","cited_by_count":1,"area":null},{"id":"2409.06945","title":"FSMDet: Vision-guided feature diffusion for fully sparse 3D detector","created":"2024-09-11","cited_by_count":1,"area":null},{"id":"2211.09518","title":"ImLiDAR: Cross-Sensor Dynamic Message Propagation Network for 3D Object Detection","created":"2022-11-17","cited_by_count":0,"area":null},{"id":"2308.13073","title":"SurGNN: Explainable visual scene understanding and assessment of surgical skill using graph neural networks","created":"2023-08-24","cited_by_count":0,"area":null},{"id":"2409.14985","title":"Image-Guided Semantic Pseudo-LiDAR Point Generation for 3D Object Detection","created":"2024-09-23","cited_by_count":0,"area":null},{"id":"2501.15449","title":"Breaking the SSL-AL Barrier: A Synergistic Semi-Supervised Active Learning Framework for 3D Object Detection","created":"2025-01-26","cited_by_count":0,"area":null},{"id":"2501.18851","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","created":"2025-01-31","cited_by_count":0,"area":null},{"id":"2512.11926","title":"TransBridge: Boost 3D Object Detection by Scene-Level Completion with Transformer Decoder","created":"2025-12-12","cited_by_count":0,"area":null}],"next_cursor":null}