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 1001–1050 of 1576 papers

TitleStatusHype
PV-SSD: A Multi-Modal Point Cloud Feature Fusion Method for Projection Features and Variable Receptive Field Voxel Features—0
Reviewing 3D Object Detectors in the Context of High-Resolution 3+1D Radar—0
An Empirical Analysis of Range for 3D Object Detection—0
FSD V2: Improving Fully Sparse 3D Object Detection with Virtual Voxels—0
QUEST: Query Stream for Practical Cooperative PerceptionCode0
MDT3D: Multi-Dataset Training for LiDAR 3D Object Detection GeneralizationCode0
MonoNext: A 3D Monocular Object Detection with ConvNext—0
HeightFormer: Explicit Height Modeling without Extra Data for Camera-only 3D Object Detection in Bird's Eye View—0
DFA3D: 3D Deformable Attention For 2D-to-3D Feature LiftingCode0
R2Det: Redemption from Range-view for Accurate 3D Object Detection—0
Improving Online Lane Graph Extraction by Object-Lane Clustering—0
SMURF: Spatial Multi-Representation Fusion for 3D Object Detection with 4D Imaging Radar—0
MLF-DET: Multi-Level Fusion for Cross-Modal 3D Object Detection—0
Ada3D : Exploiting the Spatial Redundancy with Adaptive Inference for Efficient 3D Object Detection—0
LiDAR-BEVMTN: Real-Time LiDAR Bird's-Eye View Multi-Task Perception Network for Autonomous Driving—0
Monocular 3D Object Detection with LiDAR Guided Semi Supervised Active Learning—0
S2R-ViT for Multi-Agent Cooperative Perception: Bridging the Gap from Simulation to Reality—0
KECOR: Kernel Coding Rate Maximization for Active 3D Object Detection—0
SVDM: Single-View Diffusion Model for Pseudo-Stereo 3D Object Detection—0
SUIT: Learning Significance-guided Information for 3D Temporal Detection—0
SSC3OD: Sparsely Supervised Collaborative 3D Object Detection from LiDAR Point Clouds—0
LXL: LiDAR Excluded Lean 3D Object Detection with 4D Imaging Radar and Camera Fusion—0
GMM: Delving into Gradient Aware and Model Perceive Depth Mining for Monocular 3D Detection—0
Comparative study of subset selection methods for rapid prototyping of 3D object detection algorithmsCode0
Frame Fusion with Vehicle Motion Prediction for 3D Object Detection—0
Understanding Depth Map Progressively: Adaptive Distance Interval Separation for Monocular 3d Object Detection—0
Towards a Robust Sensor Fusion Step for 3D Object Detection on Corrupted DataCode0
Improving LiDAR 3D Object Detection via Range-based Point Cloud Density Optimization—0
Weakly Supervised 3D Object Detection with Multi-Stage Generalization—0
Point-LGMask: Local and Global Contexts Embedding for Point Cloud Pre-training with Multi-Ratio MaskingCode0
Multi-View Representation is What You Need for Point-Cloud Pre-Training—0
OCBEV: Object-Centric BEV Transformer for Multi-View 3D Object Detection—0
Doubly Robust Self-TrainingCode0
CALICO: Self-Supervised Camera-LiDAR Contrastive Pre-training for BEV Perception—0
View-to-Label: Multi-View Consistency for Self-Supervised 3D Object Detection—0
Monocular 2D Camera-based Proximity Monitoring for Human-Machine Collision Warning on Construction SitesCode0
VCVW-3D: A Virtual Construction Vehicles and Workers Dataset with 3D AnnotationsCode0
Language-Guided 3D Object Detection in Point Cloud for Autonomous Driving—0
RC-BEVFusion: A Plug-In Module for Radar-Camera Bird's Eye View Feature Fusion—0
DynStatF: An Efficient Feature Fusion Strategy for LiDAR 3D Object Detection—0
RCFusion: Fusing 4-D Radar and Camera With Bird’s-Eye View Features for 3-D Object Detection—0
Real-Aug: Realistic Scene Synthesis for LiDAR Augmentation in 3D Object Detection—0
PanoContext-Former: Panoramic Total Scene Understanding with a Transformer—0
MonoTDP: Twin Depth Perception for Monocular 3D Object Detection in Adverse Scenes—0
SPADE: Sparse Pillar-based 3D Object Detection Accelerator for Autonomous Driving—0
TransCAR: Transformer-based Camera-And-Radar Fusion for 3D Object Detection—0
InfraDet3D: Multi-Modal 3D Object Detection based on Roadside Infrastructure Camera and LiDAR Sensors—0
HyperMODEST: Self-Supervised 3D Object Detection with Confidence Score FilteringCode0
Gradient-based Maximally Interfered Retrieval for Domain Incremental 3D Object DetectionCode0
OriCon3D: Effective 3D Object Detection using Orientation and Confidence—0
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All datasetsnuScenesScanNetV2SUN-RGBD valKITTI Cars EasyKITTI Cars HardnuScenes Camera OnlyKITTI Cars Easy valKITTI Cars Moderate valnuscenes Camera-RadarView-of-Delft (val)KITTI Cars Hard valDAIR-V2X-I

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