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 401–450 of 1576 papers

TitleStatusHype
3DPPE: 3D Point Positional Encoding for Multi-Camera 3D Object Detection TransformersCode1
AutoAlignV2: Deformable Feature Aggregation for Dynamic Multi-Modal 3D Object DetectionCode1
CR3DT: Camera-RADAR Fusion for 3D Detection and TrackingCode1
DI-V2X: Learning Domain-Invariant Representation for Vehicle-Infrastructure Collaborative 3D Object DetectionCode1
Object as Query: Lifting any 2D Object Detector to 3D DetectionCode1
Divide and Conquer: 3D Point Cloud Instance Segmentation With Point-Wise BinarizationCode1
High-level camera-LiDAR fusion for 3D object detection with machine learningCode1
Hindsight is 20/20: Leveraging Past Traversals to Aid 3D PerceptionCode1
HVDetFusion: A Simple and Robust Camera-Radar Fusion FrameworkCode1
OccAM's Laser: Occlusion-based Attribution Maps for 3D Object Detectors on LiDAR DataCode1
GUPNet++: Geometry Uncertainty Propagation Network for Monocular 3D Object DetectionCode1
ODAM: Object Detection, Association, and Mapping using Posed RGB VideoCode1
H3DNet: 3D Object Detection Using Hybrid Geometric PrimitivesCode1
Among Us: Adversarially Robust Collaborative Perception by ConsensusCode1
Group-Free 3D Object Detection via TransformersCode1
3D Cascade RCNN: High Quality Object Detection in Point CloudsCode1
A Multimodal Hybrid Late-Cascade Fusion Network for Enhanced 3D Object DetectionCode1
CoreNet: Conflict Resolution Network for Point-Pixel Misalignment and Sub-Task Suppression of 3D LiDAR-Camera Object DetectionCode1
GSPN: Generative Shape Proposal Network for 3D Instance Segmentation in Point CloudCode1
3DRM:Pair-wise relation module for 3D object detectionCode1
Harnessing Uncertainty-aware Bounding Boxes for Unsupervised 3D Object DetectionCode1
CORE: Cooperative Reconstruction for Multi-Agent PerceptionCode1
Graph R-CNN: Towards Accurate 3D Object Detection with Semantic-Decorated Local GraphCode1
DSGN: Deep Stereo Geometry Network for 3D Object DetectionCode1
DSGN++: Exploiting Visual-Spatial Relation for Stereo-based 3D DetectorsCode1
3D Small Object Detection with Dynamic Spatial PruningCode1
GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Monocular 3D Object DetectionCode1
GO-N3RDet: Geometry Optimized NeRF-enhanced 3D Object DetectorCode1
DualDiff+: Dual-Branch Diffusion for High-Fidelity Video Generation with Reward GuidanceCode1
DualDiff: Dual-branch Diffusion Model for Autonomous Driving with Semantic FusionCode1
Bridging the Domain Gap: Self-Supervised 3D Scene Understanding with Foundation ModelsCode1
Physical Attack on Monocular Depth Estimation with Optimal Adversarial PatchesCode1
3D-MPA: Multi Proposal Aggregation for 3D Semantic Instance SegmentationCode1
Dual Radar: A Multi-modal Dataset with Dual 4D Radar for Autonomous DrivingCode1
3D Object Detection for Autonomous Driving: A SurveyCode1
GPA-3D: Geometry-aware Prototype Alignment for Unsupervised Domain Adaptive 3D Object Detection from Point CloudsCode1
An End-to-End Transformer Model for 3D Object DetectionCode1
Ground-aware Monocular 3D Object Detection for Autonomous DrivingCode1
HEDNet: A Hierarchical Encoder-Decoder Network for 3D Object Detection in Point CloudsCode1
HVPR: Hybrid Voxel-Point Representation for Single-stage 3D Object DetectionCode1
CAGroup3D: Class-Aware Grouping for 3D Object Detection on Point CloudsCode1
DynOPETs: A Versatile Benchmark for Dynamic Object Pose Estimation and Tracking in Moving Camera ScenariosCode1
CaKDP: Category-aware Knowledge Distillation and Pruning Framework for Lightweight 3D Object DetectionCode1
Point Cloud Pre-Training With Natural 3D StructuresCode1
Learning Auxiliary Monocular Contexts Helps Monocular 3D Object DetectionCode1
EarlyBird: Early-Fusion for Multi-View Tracking in the Bird's Eye ViewCode1
GeoBEV: Learning Geometric BEV Representation for Multi-view 3D Object DetectionCode1
Attentive Prototypes for Source-free Unsupervised Domain Adaptive 3D Object DetectionCode1
Canadian Adverse Driving Conditions DatasetCode1
General Geometry-aware Weakly Supervised 3D Object DetectionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1EA-LSSNDS0.78—Unverified
2MegFusionNDS0.77—Unverified
3MMFusion-eNDS0.77—Unverified
4BEVFusion-eNDS0.76—Unverified
5RacoonPowerNDS0.76—Unverified
6DeepInteraction-largeNDS0.76—Unverified
7DeepInteraction-eNDS0.76—Unverified
8FusionVPENDS0.75—Unverified
9FocalFormer3D-FNDS0.75—Unverified
10CenterPoint-FusionNDS0.75—Unverified