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 201–225 of 1576 papers

TitleStatusHype
ALPI: Auto-Labeller with Proxy Injection for 3D Object Detection using 2D Labels OnlyCode1
What Matters in Range View 3D Object DetectionCode1
Learning High-resolution Vector Representation from Multi-Camera Images for 3D Object DetectionCode1
General Geometry-aware Weakly Supervised 3D Object DetectionCode1
RepVF: A Unified Vector Fields Representation for Multi-task 3D PerceptionCode1
LabelDistill: Label-guided Cross-modal Knowledge Distillation for Camera-based 3D Object DetectionCode1
FSD-BEV: Foreground Self-Distillation for Multi-view 3D Object DetectionCode1
Approaching Outside: Scaling Unsupervised 3D Object Detection from 2D SceneCode1
MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object DetectionCode1
Learning Shared RGB-D Fields: Unified Self-supervised Pre-training for Label-efficient LiDAR-Camera 3D PerceptionCode1
DiffuBox: Refining 3D Object Detection with Point DiffusionCode1
UNION: Unsupervised 3D Object Detection using Object Appearance-based Pseudo-ClassesCode1
FADet: A Multi-sensor 3D Object Detection Network based on Local Featured AttentionCode1
Reliable Student: Addressing Noise in Semi-Supervised 3D Object DetectionCode1
Revisiting Out-of-Distribution Detection in LiDAR-based 3D Object DetectionCode1
Better Monocular 3D Detectors with LiDAR from the PastCode1
MonoTAKD: Teaching Assistant Knowledge Distillation for Monocular 3D Object DetectionCode1
VSRD: Instance-Aware Volumetric Silhouette Rendering for Weakly Supervised 3D Object DetectionCode1
UADA3D: Unsupervised Adversarial Domain Adaptation for 3D Object Detection with Sparse LiDAR and Large Domain GapsCode1
CR3DT: Camera-RADAR Fusion for 3D Detection and TrackingCode1
Find n' Propagate: Open-Vocabulary 3D Object Detection in Urban EnvironmentsCode1
SimPB: A Single Model for 2D and 3D Object Detection from Multiple CamerasCode1
Unleashing HyDRa: Hybrid Fusion, Depth Consistency and Radar for Unified 3D PerceptionCode1
Fine-Grained Pillar Feature Encoding Via Spatio-Temporal Virtual Grid for 3D Object DetectionCode1
SeSame: Simple, Easy 3D Object Detection with Point-Wise SemanticsCode1
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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