SOTAVerified

3D Object Detection

3D Object Detection is a task in computer vision where the goal is to identify and locate objects in a 3D environment based on their shape, location, and orientation. It involves detecting the presence of objects and determining their location in the 3D space in real-time. This task is crucial for applications such as autonomous vehicles, robotics, and augmented reality.

( Image credit: AVOD )

Papers

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Showing 701–750 of 1576 papers

TitleStatusHype
TREND: Unsupervised 3D Representation Learning via Temporal Forecasting for LiDAR Perception—0
Redundant Queries in DETR-Based 3D Detection Methods: Unnecessary and PrunableCode0
MCBLT: Multi-Camera Multi-Object 3D Tracking in Long Videos—0
SpaRC: Sparse Radar-Camera Fusion for 3D Object DetectionCode0
Training an Open-Vocabulary Monocular 3D Object Detection Model without 3D Data—0
MSSF: A 4D Radar and Camera Fusion Framework With Multi-Stage Sampling for 3D Object Detection in Autonomous Driving—0
VisionPAD: A Vision-Centric Pre-training Paradigm for Autonomous Driving—0
VADet: Multi-frame LiDAR 3D Object Detection using Variable Aggregation—0
MambaDETR: Query-based Temporal Modeling using State Space Model for Multi-View 3D Object Detection—0
EVT: Efficient View Transformation for Multi-Modal 3D Object Detection—0
Methodology for a Statistical Analysis of Influencing Factors on 3D Object Detection Performance—0
Efficient 3D Perception on Multi-Sweep Point Cloud with Gumbel Spatial Pruning—0
SimpleBEV: Improved LiDAR-Camera Fusion Architecture for 3D Object Detection—0
ZOPP: A Framework of Zero-shot Offboard Panoptic Perception for Autonomous Driving—0
Self-supervised cross-modality learning for uncertainty-aware object detection and recognition in applications which lack pre-labelled training data—0
One for All: Multi-Domain Joint Training for Point Cloud Based 3D Object Detection—0
GAFusion: Adaptive Fusing LiDAR and Camera with Multiple Guidance for 3D Object Detection—0
HD-OOD3D: Supervised and Unsupervised Out-of-Distribution object detection in LiDAR data—0
Uncertainty Estimation for 3D Object Detection via Evidential Learning—0
EMMA: End-to-End Multimodal Model for Autonomous Driving—0
S3PT: Scene Semantics and Structure Guided Clustering to Boost Self-Supervised Pre-Training for Autonomous Driving—0
Unified Domain Generalization and Adaptation for Multi-View 3D Object Detection—0
DECADE: Towards Designing Efficient-yet-Accurate Distance Estimation Modules for Collision Avoidance in Mobile Advanced Driver Assistance Systems—0
SAM-Guided Masked Token Prediction for 3D Scene Understanding—0
MambaBEV: An efficient 3D detection model with Mamba2—0
Cocoon: Robust Multi-Modal Perception with Uncertainty-Aware Sensor Fusion—0
CVCP-Fusion: On Implicit Depth Estimation for 3D Bounding Box PredictionCode0
ROA-BEV: 2D Region-Oriented Attention for BEV-based 3D Object—0
UAV3D: A Large-scale 3D Perception Benchmark for Unmanned Aerial Vehicles—0
HeightFormer: A Semantic Alignment Monocular 3D Object Detection Method from Roadside Perspective—0
Progressive Multi-Modal Fusion for Robust 3D Object Detection—0
QuadBEV: An Efficient Quadruple-Task Perception Framework via Bird's-Eye-View Representation—0
STONE: A Submodular Optimization Framework for Active 3D Object DetectionCode0
Learning 3D Perception from Others' Predictions—0
Panopticus: Omnidirectional 3D Object Detection on Resource-constrained Edge Devices—0
Gaussian-Det: Learning Closed-Surface Gaussians for 3D Object Detection—0
Finetuning Pre-trained Model with Limited Data for LiDAR-based 3D Object Detection by Bridging Domain Gaps—0
Can We Remove the Ground? Obstacle-aware Point Cloud Compression for Remote Object Detection—0
VLMine: Long-Tail Data Mining with Vision Language Models—0
Sparse-to-Dense LiDAR Point Generation by LiDAR-Camera Fusion for 3D Object Detection—0
UniBEVFusion: Unified Radar-Vision BEVFusion for 3D Object Detection—0
TrajSSL: Trajectory-Enhanced Semi-Supervised 3D Object Detection—0
Unleashing the Potential of Mamba: Boosting a LiDAR 3D Sparse Detector by Using Cross-Model Knowledge Distillation—0
Directed-CP: Directed Collaborative Perception for Connected and Autonomous Vehicles via Proactive Attention—0
Semi-Supervised 3D Object Detection with Channel Augmentation using Transformation Equivariance—0
Cross-Modal Self-Supervised Learning with Effective Contrastive Units for LiDAR Point CloudsCode0
Distribution Discrepancy and Feature Heterogeneity for Active 3D Object DetectionCode0
RCBEVDet++: Toward High-accuracy Radar-Camera Fusion 3D Perception Network—0
Multi-V2X: A Large Scale Multi-modal Multi-penetration-rate Dataset for Cooperative PerceptionCode0
Multi-scale Feature Fusion with Point Pyramid for 3D Object Detection—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1EA-LSSNDS0.78—Unverified
2MMFusion-eNDS0.77—Unverified
3MegFusionNDS0.77—Unverified
4RacoonPowerNDS0.76—Unverified
5BEVFusion-eNDS0.76—Unverified
6DeepInteraction-largeNDS0.76—Unverified
7DeepInteraction-eNDS0.76—Unverified
8DAANDS0.75—Unverified
9FusionVPENDS0.75—Unverified
10CenterPoint-FusionNDS0.75—Unverified