{"total":151,"rows":[{"id":"2403.18913","title":"UniDepth: Universal Monocular Metric Depth Estimation","created":"2024-03-27","cited_by_count":382,"area":null},{"id":"2108.06417","title":"Is Pseudo-Lidar needed for Monocular 3D Object detection?","created":"2021-08-13","cited_by_count":249,"area":null},{"id":"2106.11037","title":"One Million Scenes for Autonomous Driving: ONCE Dataset","created":"2021-06-21","cited_by_count":218,"area":null},{"id":"2502.20110","title":"UniDepthV2: Universal Monocular Metric Depth Estimation Made Simpler","created":"2025-02-27","cited_by_count":173,"area":null},{"id":"2103.05346","title":"ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object Detection","created":"2021-03-09","cited_by_count":159,"area":null},{"id":"2206.09474","title":"3D Object Detection for Autonomous Driving: A Comprehensive Survey","created":"2022-06-19","cited_by_count":132,"area":null},{"id":"2112.00463","title":"The Norm Must Go On: Dynamic Unsupervised Domain Adaptation by Normalization","created":"2021-12-01","cited_by_count":131,"area":null},{"id":"2206.08171","title":"K-Radar: 4D Radar Object Detection for Autonomous Driving in Various Weather Conditions","created":"2022-06-16","cited_by_count":108,"area":null},{"id":"2108.06709","title":"SPG: Unsupervised Domain Adaptation for 3D Object Detection via Semantic Point Generation","created":"2021-08-15","cited_by_count":94,"area":null},{"id":"2201.10830","title":"MonoDistill: Learning Spatial Features for Monocular 3D Object Detection","created":"2022-01-26","cited_by_count":68,"area":null},{"id":"2202.02980","title":"3D Object Detection from Images for Autonomous Driving: A Survey","created":"2022-02-07","cited_by_count":66,"area":null},{"id":"2107.11355","title":"Unsupervised Domain Adaptive 3D Detection with Multi-Level Consistency","created":"2021-07-23","cited_by_count":63,"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":"2108.06682","title":"ST3D++: Denoised Self-training for Unsupervised Domain Adaptation on 3D Object Detection","created":"2021-08-15","cited_by_count":57,"area":null},{"id":"2203.14956","title":"LiDAR Distillation: Bridging the Beam-Induced Domain Gap for 3D Object Detection","created":"2022-03-28","cited_by_count":55,"area":null},{"id":"2207.10758","title":"DEVIANT: Depth EquiVarIAnt NeTwork for Monocular 3D Object Detection","created":"2022-07-21","cited_by_count":48,"area":null},{"id":"2403.13129","title":"Better Call SAL: Towards Learning to Segment Anything in Lidar","created":"2024-03-19","cited_by_count":47,"area":null},{"id":"2203.15882","title":"Learning to Detect Mobile Objects from LiDAR Scans Without Labels","created":"2022-03-29","cited_by_count":44,"area":null},{"id":"2112.04764","title":"3D-VField: Adversarial Augmentation of Point Clouds for Domain Generalization in 3D Object Detection","created":"2021-12-09","cited_by_count":43,"area":null},{"id":"2212.02845","title":"SSDA3D: Semi-supervised Domain Adaptation for 3D Object Detection from Point Cloud","created":"2022-12-06","cited_by_count":37,"area":null},{"id":"2103.02093","title":"Pseudo-labeling for Scalable 3D Object Detection","created":"2021-03-02","cited_by_count":32,"area":null},{"id":"2304.09446","title":"Density-Insensitive Unsupervised Domain Adaption on 3D Object Detection","created":"2023-04-19","cited_by_count":31,"area":null},{"id":"2108.07142","title":"PIT: Position-Invariant Transform for Cross-FoV Domain Adaptation","created":"2021-08-16","cited_by_count":30,"area":null},{"id":"2203.16895","title":"Deformation and Correspondence Aware Unsupervised Synthetic-to-Real Scene Flow Estimation for Point Clouds","created":"2022-03-31","cited_by_count":28,"area":null},{"id":"2307.07944","title":"Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-Labeling","created":"2023-07-16","cited_by_count":28,"area":null},{"id":"2309.13549","title":"Towards Robust Robot 3D Perception in Urban Environments: The UT Campus Object Dataset","created":"2023-09-24","cited_by_count":28,"area":null},{"id":"2212.00244","title":"CL3D: Unsupervised Domain Adaptation for Cross-LiDAR 3D Detection","created":"2022-12-01","cited_by_count":27,"area":null},{"id":"2207.04587","title":"Gradual Domain Adaptation without Indexed Intermediate Domains","created":"2022-07-11","cited_by_count":26,"area":null},{"id":"2103.15326","title":"Fooling LiDAR Perception via Adversarial Trajectory Perturbation","created":"2021-03-29","cited_by_count":25,"area":null},{"id":"2211.11432","title":"MATE: Masked Autoencoders are Online 3D Test-Time Learners","created":"2022-11-21","cited_by_count":23,"area":null},{"id":"2303.05886","title":"Bi3D: Bi-domain Active Learning for Cross-domain 3D Object Detection","created":"2023-03-10","cited_by_count":22,"area":null},{"id":"2406.07661","title":"ROADWork: A Dataset and Benchmark for Learning to Recognize, Observe, Analyze and Drive Through Work Zones","created":"2024-06-11","cited_by_count":22,"area":null},{"id":"2103.14198","title":"Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection","created":"2021-03-26","cited_by_count":21,"area":null},{"id":"2304.03251","title":"SALUDA: Surface-based Automotive Lidar Unsupervised Domain Adaptation","created":"2023-04-06","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":"2306.00612","title":"AD-PT: Autonomous Driving Pre-Training with Large-scale Point Cloud Dataset","created":"2023-06-01","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":"2305.19812","title":"A Survey of Label-Efficient Deep Learning for 3D Point Clouds","created":"2023-05-31","cited_by_count":20,"area":null},{"id":"2109.14651","title":"Uncertainty-aware Mean Teacher for Source-free Unsupervised Domain Adaptive 3D Object Detection","created":"2021-09-29","cited_by_count":18,"area":null},{"id":"2507.17665","title":"Perspective-Invariant 3D Object Detection","created":"2025-07-23","cited_by_count":18,"area":"wm"},{"id":"2303.15443","title":"GeoNet: Benchmarking Unsupervised Adaptation across Geographies","created":"2023-03-27","cited_by_count":17,"area":null},{"id":"2310.08117","title":"DUSA: Decoupled Unsupervised Sim2Real Adaptation for Vehicle-to-Everything Collaborative Perception","created":"2023-10-12","cited_by_count":17,"area":null},{"id":"2110.00464","title":"MonoCInIS: Camera Independent Monocular 3D Object Detection using Instance Segmentation","created":"2021-10-01","cited_by_count":16,"area":null},{"id":"2111.09450","title":"See Eye to Eye: A Lidar-Agnostic 3D Detection Framework for Unsupervised Multi-Target Domain Adaptation","created":"2021-11-17","cited_by_count":15,"area":null},{"id":"2308.01000","title":"MDT3D: Multi-Dataset Training for LiDAR 3D Object Detection Generalization","created":"2023-08-02","cited_by_count":14,"area":null},{"id":"2308.05988","title":"MS3D++: Ensemble of Experts for Multi-Source Unsupervised Domain Adaptation in 3D Object Detection","created":"2023-08-11","cited_by_count":14,"area":null},{"id":"2310.19080","title":"Reward Finetuning for Faster and More Accurate Unsupervised Object Discovery","created":"2023-10-29","cited_by_count":14,"area":"alignment"},{"id":"2403.18442","title":"Backpropagation-free Network for 3D Test-time Adaptation","created":"2024-03-27","cited_by_count":14,"area":null},{"id":"2111.15656","title":"Attentive Prototypes for Source-free Unsupervised Domain Adaptive 3D Object Detection","created":"2021-11-30","cited_by_count":13,"area":null},{"id":"2204.01599","title":"DODA: Data-oriented Sim-to-Real Domain Adaptation for 3D Semantic Segmentation","created":"2022-04-04","cited_by_count":13,"area":null},{"id":"2301.12515","title":"LiDAR-CS Dataset: LiDAR Point Cloud Dataset with Cross-Sensors for 3D Object Detection","created":"2023-01-29","cited_by_count":13,"area":null},{"id":"2303.15286","title":"Unsupervised Adaptation from Repeated Traversals for Autonomous Driving","created":"2023-03-27","cited_by_count":13,"area":null},{"id":"2304.11705","title":"Walking Your LiDOG: A Journey Through Multiple Domains for LiDAR Semantic Segmentation","created":"2023-04-23","cited_by_count":13,"area":null},{"id":"2309.05527","title":"ReSimAD: Zero-Shot 3D Domain Transfer for Autonomous Driving with Source Reconstruction and Target Simulation","created":"2023-09-11","cited_by_count":13,"area":null},{"id":"2404.16493","title":"Commonsense Prototype for Outdoor Unsupervised 3D Object Detection","created":"2024-04-25","cited_by_count":13,"area":null},{"id":"2410.22461","title":"Unified Domain Generalization and Adaptation for Multi-View 3D Object Detection","created":"2024-10-29","cited_by_count":13,"area":null},{"id":"2503.16707","title":"Cross-Modal and Uncertainty-Aware Agglomeration for Open-Vocabulary 3D Scene Understanding","created":"2025-03-20","cited_by_count":13,"area":"mllm"},{"id":"2304.02431","title":"MS3D: Leveraging Multiple Detectors for Unsupervised Domain Adaptation in 3D Object Detection","created":"2023-04-05","cited_by_count":12,"area":null},{"id":"2403.17633","title":"UADA3D: Unsupervised Adversarial Domain Adaptation for 3D Object Detection with Sparse LiDAR and Large Domain Gaps","created":"2024-03-26","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":"2104.11021","title":"Cycle and Semantic Consistent Adversarial Domain Adaptation for Reducing Simulation-to-Real Domain Shift in LiDAR Bird's Eye View","created":"2021-04-22","cited_by_count":10,"area":null},{"id":"2110.09355","title":"FAST3D: Flow-Aware Self-Training for 3D Object Detectors","created":"2021-10-18","cited_by_count":10,"area":null},{"id":"2204.00106","title":"A Survey of Robust 3D Object Detection Methods in Point Clouds","created":"2022-03-31","cited_by_count":10,"area":null},{"id":"2204.00132","title":"Real-Time and Robust 3D Object Detection Within Road-Side LiDARs Using Domain Adaptation","created":"2022-03-31","cited_by_count":10,"area":null},{"id":"2209.06407","title":"Viewer-Centred Surface Completion for Unsupervised Domain Adaptation in 3D Object Detection","created":"2022-09-14","cited_by_count":10,"area":null},{"id":"2402.17562","title":"An Empirical Study of the Generalization Ability of Lidar 3D Object Detectors to Unseen Domains","created":"2024-02-27","cited_by_count":10,"area":null},{"id":"2210.05896","title":"Common Corruption Robustness of Point Cloud Detectors: Benchmark and Enhancement","created":"2022-10-12","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":"2204.11122","title":"Can domain adaptation make object recognition work for everyone?","created":"2022-04-23","cited_by_count":8,"area":null},{"id":"2308.08140","title":"GPA-3D: Geometry-aware Prototype Alignment for Unsupervised Domain Adaptive 3D Object Detection from Point Clouds","created":"2023-08-16","cited_by_count":8,"area":null},{"id":"2401.04230","title":"SOAP: Cross-sensor Domain Adaptation for 3D Object Detection Using Stationary Object Aggregation Pseudo-labelling","created":"2024-01-08","cited_by_count":8,"area":null},{"id":"2403.03721","title":"CMDA: Cross-Modal and Domain Adversarial Adaptation for LiDAR-Based 3D Object Detection","created":"2024-03-06","cited_by_count":8,"area":null},{"id":"2404.11764","title":"Multimodal 3D Object Detection on Unseen Domains","created":"2024-04-17","cited_by_count":8,"area":null},{"id":"2301.01615","title":"StereoDistill: Pick the Cream from LiDAR for Distilling Stereo-based 3D Object Detection","created":"2023-01-04","cited_by_count":7,"area":null},{"id":"2303.01899","title":"Quantifying the LiDAR Sim-to-Real Domain Shift: A Detailed Investigation Using Object Detectors and Analyzing Point Clouds at Target-Level","created":"2023-03-03","cited_by_count":7,"area":null},{"id":"2404.19384","title":"Pseudo Label Refinery for Unsupervised Domain Adaptation on Cross-dataset 3D Object Detection","created":"2024-04-30","cited_by_count":7,"area":null},{"id":"2405.16034","title":"DiffuBox: Refining 3D Object Detection with Point Diffusion","created":"2024-05-25","cited_by_count":7,"area":null},{"id":"2406.14878","title":"MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object Detection","created":"2024-06-21","cited_by_count":7,"area":null},{"id":"2205.11664","title":"Towards Model Generalization for Monocular 3D Object Detection","created":"2022-05-23","cited_by_count":6,"area":null},{"id":"2311.10845","title":"Domain Generalization of 3D Object Detection by Density-Resampling","created":"2023-11-17","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":"2409.04409","title":"Train Till You Drop: Towards Stable and Robust Source-free Unsupervised 3D Domain Adaptation","created":"2024-09-06","cited_by_count":6,"area":null},{"id":"2508.11185","title":"CHARM3R: Towards Unseen Camera Height Robust Monocular 3D Detector","created":"2025-08-15","cited_by_count":6,"area":null},{"id":"2310.16542","title":"ParisLuco3D: A high-quality target dataset for domain generalization of LiDAR perception","created":"2023-10-25","cited_by_count":5,"area":null},{"id":"2403.11691","title":"TTT-KD: Test-Time Training for 3D Semantic Segmentation through Knowledge Distillation from Foundation Models","created":"2024-03-18","cited_by_count":5,"area":"distill"},{"id":"2406.13891","title":"DPO: Dual-Perturbation Optimization for Test-time Adaptation in 3D Object Detection","created":"2024-06-19","cited_by_count":5,"area":null},{"id":"2409.07887","title":"UNIT: Unsupervised Online Instance Segmentation through Time","created":"2024-09-12","cited_by_count":5,"area":null},{"id":"2410.23910","title":"Uncertainty Estimation for 3D Object Detection via Evidential Learning","created":"2024-10-31","cited_by_count":5,"area":null},{"id":"2210.02493","title":"Depth Is All You Need for Monocular 3D Detection","created":"2022-10-05","cited_by_count":4,"area":null},{"id":"2210.07811","title":"SAILOR: Scaling Anchors via Insights into Latent Object Representation","created":"2022-10-14","cited_by_count":4,"area":null},{"id":"2212.02057","title":"DA-CIL: Towards Domain Adaptive Class-Incremental 3D Object Detection","created":"2022-12-05","cited_by_count":4,"area":null},{"id":"2308.15479","title":"3D Adversarial Augmentations for Robust Out-of-Domain Predictions","created":"2023-08-29","cited_by_count":4,"area":null},{"id":"2401.01482","title":"Incorporating Geo-Diverse Knowledge into Prompting for Increased Geographical Robustness in Object Recognition","created":"2024-01-03","cited_by_count":4,"area":null},{"id":"2407.04061","title":"Detect Closer Surfaces that can be Seen: New Modeling and Evaluation in Cross-domain 3D Object Detection","created":"2024-07-04","cited_by_count":4,"area":null},{"id":"2410.02646","title":"Learning 3D Perception from Others' Predictions","created":"2024-10-03","cited_by_count":4,"area":null},{"id":"2412.05548","title":"Street Gaussians without 3D Object Tracker","created":"2024-12-07","cited_by_count":4,"area":null},{"id":"2412.08806","title":"DALI: Domain Adaptive LiDAR Object Detection via Distribution-level and Instance-level Pseudo Label Denoising","created":"2024-12-11","cited_by_count":4,"area":null},{"id":"2503.12150","title":"Point-Cache: Test-time Dynamic and Hierarchical Cache for Robust and Generalizable Point Cloud Analysis","created":"2025-03-15","cited_by_count":4,"area":null},{"id":"2202.13505","title":"Cyber Mobility Mirror: A Deep Learning-based Real-World Object Perception Platform Using Roadside LiDAR","created":"2022-02-28","cited_by_count":3,"area":null},{"id":"2211.11950","title":"UpCycling: Semi-supervised 3D Object Detection without Sharing Raw-level Unlabeled Scenes","created":"2022-11-22","cited_by_count":3,"area":null}],"next_cursor":"100"}