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

Showing 1–10 of 1576 papers

TitleStatusHype
Dual LiDAR-Based Traffic Movement Count Estimation at a Signalized Intersection: Deployment, Data Collection, and Preliminary Analysis—0
Beyond One Shot, Beyond One Perspective: Cross-View and Long-Horizon Distillation for Better LiDAR RepresentationsCode1
MambaFusion: Height-Fidelity Dense Global Fusion for Multi-modal 3D Object DetectionCode2
A Survey of Multi-sensor Fusion Perception for Embodied AI: Background, Methods, Challenges and Prospects—0
Vision-based Lifting of 2D Object Detections for Automated Driving—0
Teleoperated Driving: a New Challenge for 3D Object Detection in Compressed Point Clouds—0
DySS: Dynamic Queries and State-Space Learning for Efficient 3D Object Detection from Multi-Camera Videos—0
Gaussian2Scene: 3D Scene Representation Learning via Self-supervised Learning with 3D Gaussian Splatting—0
Cosmos-Drive-Dreams: Scalable Synthetic Driving Data Generation with World Foundation ModelsCode3
SpikeSMOKE: Spiking Neural Networks for Monocular 3D Object Detection with Cross-Scale Gated Coding—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TRTConvAP80.38—Unverified
23D Dual-FusionAP79.39—Unverified
3GLENet-VRAP78.43—Unverified
4PV-RCNN++AP77.15—Unverified
5Voxel R-CNNAP77.06—Unverified
6M3DeTRAP76.96—Unverified
7PC-RGNNAP75.54—Unverified
8SVGA-NetAP74.63—Unverified
9JointAP74.3—Unverified
10SA-SSD+EBMAP72.78—Unverified