Papers 3D Object Detection
“3D Object Detection” 태그가 달린 논문 1,801편 · 필터 해제
NeuroSymbEAD: A Large Scale Neuro-Symbolic Caption Dataset for Omni-Directional Embodied Autonomous Driving
This paper introduces NeuroSymbEAD, a large-scale neuro-symbolic caption dataset featuring an ego-centric knowledge graph (KG) of static and dynamic objects annotated with classes, categories, heading directions, orienta…
Scene Understanding3D Object DetectionAutonomous DrivingSimFuse3D: Source-Guided Target Simulation and Confidence-Guided Multi-Stage Localization Reweighting for Cross-Platform 3D Object Detection
Changes in sensor height and viewpoint alter object-level point distributions, making cross-platform LiDAR unsupervised domain adaptation (UDA) difficult. Self-training uses labeled source scans and unlabeled target scan…
Unsupervised Domain Adaptation3D Object DetectionLucida: Parse, Generate, and Place for Composable Real-to-Sim Scene Modeling
Composable scene modeling aims to recover a real indoor scene as complete, editable object assets arranged as observed, giving robot simulation and embodied AI a simulation-ready replica of the real environment whose obj…
3D Object DetectionPose EstimationQwen-Drive-1.0: An Initial Step towards a Vision-Language Foundation Model for Autonomous Driving
We present Qwen-Drive-1.0, an initial step towards a vision-language foundation model for autonomous driving. Qwen-Drive-1.0 retains the architecture of the pretrained vision-language model (VLM) and integrates 3D percep…
Visual Question AnsweringScene Understanding3D Object DetectionAutonomous DrivingTADP: Task-Aware Deformable Prediction for Single-Stage 3D Object Detection
Most single-stage 3D object detectors complete different tasks with the same extracted features. Nevertheless, it is impossible to project features into a common space that is adaptive for all the tasks. We present a nov…
3D Object DetectionOpen-Vocabulary 3D Object Detection with Co-Distillation Discovery and Dual Guidance Robust Training
Recently, open-vocabulary 3D object detection (3D-OVD) has gained increasing attention for its ability to detect unseen objects in 3D scenes. Existing approaches typically adopt a two-stage pipeline that first discovers …
3D Object DetectionGhostPoint: Self-Supervised Representation Learning by Hallucinating Occluded LiDAR Structure
3D object detection from LiDAR point clouds is a core problem in autonomous driving. Recent advances in self-supervised learning (SSL) enable scalable pretraining and transfers well to per-point tasks such as semantic an…
Self-Supervised LearningRepresentation LearningPanoptic Segmentation3D Object DetectionMAGneT-3D: Monocular and Domain-Generalizable Temporal 3D Detection
Monocular temporal 3D detection aims to detect objects in 3D, given a monocular video. Query-based 3D detectors unify detection and cross-view association, but their learnable queries fit the spatial distribution of the …
Domain Generalization3D Object DetectionGeometry-Grounded Unified 3D Perception for Autonomous Driving
Camera-based autonomous driving perception requires a shared representation that preserves metric 3D structure across synchronized multi-camera streams. However, existing image-based frameworks often rely on backbones pr…
3D Object DetectionAutonomous DrivingDepth EstimationLightweight 3D Object Detection via Mamba-Based Knowledge Distillation
3D object detection using light detection and ranging (LiDAR) sensors requires a balance between accuracy and computational efficiency for onboard perception in autonomous driving and robotic navigation. Many existing Li…
Computational EfficiencyKnowledge Distillation3D Object DetectionAutonomous DrivingRadYOLO: Computationally Efficient 3D Object Detection and Segmentation in CT and MRI
Object detection and segmentation in three-dimensional medical images is a very active area of research. However, most proposed deep learning models carry a high computational cost, and only few aim to be broadly applica…
3D Object DetectionObject LocalizationMulti-Sensor Alignment for Weather Simulations
Perception tasks for autonomous vehicles need to work satisfactorily in adverse weather conditions. Due to lack of real-world weather datasets, weather simulations are a promising alternative. To ensure simulations close…
3D Object DetectionAutonomous VehiclesRECO: Region-Aware Compensation for Extrinsic Perturbations in Roadside 3D Detection
In intelligent transportation systems, roadside 3D object detection provides wide-area perception crucial for traffic understanding, cooperative early warning, and safe autonomous driving. However, existing methods suffe…
3D Object DetectionAutonomous DrivingBreaking the Model Forgetting Cycle in Long-Incremental 3D Object Detection
Incremental 3D object detection requires a detector to learn novel object classes while remembering previously learned ones over sequentially arriving data. Previous methods, primarily based on pseudo-labeling, perform r…
3D Object DetectionDeGuNet: Depth-Guided Ultra-Compact Backbones for Efficient LiDAR-Camera 3D Detection
In autonomous driving perception, the fusion of LiDAR and camera modalities has become the dominant paradigm for 3D object detection. However, current multi-modal frameworks heavily rely on massive visual backbones pretr…
Representation Learning3D Object DetectionAutonomous DrivingOn Exploring Input Resolution Scaling For Anytime LiDAR Object Detection
Making tradeoffs between execution latency and result utility (i.e., anytime computing) for adapting to dynamic operational requirements has been shown to enhance the performance of cyber-physical systems. In this work, …
3D Object DetectionAutonomous DrivingPoint CloudsSparse4D-Radar: An Efficient and Robust Framework for Surround-View 3D Object Detection via 4D Radar-Camera Fusion
In recent years, 4D imaging radar has gained wide attention in autonomous driving for its robustness against harsh weather and ability to output target velocity. Nevertheless, mainstream 4D radar-camera fusion methods on…
3D Object DetectionAutonomous DrivingFramework and Multi-modal Dataset for Roadwork Zone Detection and Geo-localization
Autonomous vehicles often rely on high-definition (HD) maps for navigation; however, these maps are not frequently updated and often lack semi-static information, such as temporary roadwork zones, which can significantly…
Semantic Segmentation3D Object DetectionAutonomous VehiclesAutonomous DrivingComprehensive Robustness Analysis of LiDAR-based 3D Object Detection in Autonomous Driving
Recent advancements in LiDAR-only 3D object detection have demonstrated improved detection accuracy over benchmark datasets. However, the adversarial robustness of these models remains untested. Very few adversarial robu…
Adversarial Robustness3D Object DetectionAutonomous DrivingA Stereo Visual SLAM System Using Object-Level Motion Estimation and Geometric Filtering Based on Cross Disparity
This paper presents OCD SLAM, a dynamic stereo visual SLAM framework that extends ORB-SLAM2 by jointly addressing dynamic objects and dynamic features in the scene. Usual visual SLAM systems operating in dynamic environm…
3D Object DetectionObject TrackingPose Estimation