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 7180 of 1576 papers

TitleStatusHype
DetZero: Rethinking Offboard 3D Object Detection with Long-term Sequential Point CloudsCode2
EFFOcc: A Minimal Baseline for EFficient Fusion-based 3D Occupancy NetworkCode2
DAIR-V2X: A Large-Scale Dataset for Vehicle-Infrastructure Cooperative 3D Object DetectionCode2
Complex-YOLO: Real-time 3D Object Detection on Point CloudsCode2
DEVIANT: Depth EquiVarIAnt NeTwork for Monocular 3D Object DetectionCode2
DiffBEV: Conditional Diffusion Model for Bird's Eye View PerceptionCode2
Commonsense Prototype for Outdoor Unsupervised 3D Object DetectionCode2
A Simple Framework for 3D Occupancy Estimation in Autonomous DrivingCode2
DAOcc: 3D Object Detection Assisted Multi-Sensor Fusion for 3D Occupancy PredictionCode2
CoBEVT: Cooperative Bird's Eye View Semantic Segmentation with Sparse TransformersCode2
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Benchmark Results

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