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 4150 of 1576 papers

TitleStatusHype
RockTrack: A 3D Robust Multi-Camera-Ken Multi-Object Tracking FrameworkCode2
UniDet3D: Multi-dataset Indoor 3D Object DetectionCode2
L4DR: LiDAR-4DRadar Fusion for Weather-Robust 3D Object DetectionCode2
MonoWAD: Weather-Adaptive Diffusion Model for Robust Monocular 3D Object DetectionCode2
OPEN: Object-wise Position Embedding for Multi-view 3D Object DetectionCode2
When Pedestrian Detection Meets Multi-Modal Learning: Generalist Model and Benchmark DatasetCode2
Voxel Mamba: Group-Free State Space Models for Point Cloud based 3D Object DetectionCode2
EFM3D: A Benchmark for Measuring Progress Towards 3D Egocentric Foundation ModelsCode2
BEVSpread: Spread Voxel Pooling for Bird's-Eye-View Representation in Vision-based Roadside 3D Object DetectionCode2
EFFOcc: A Minimal Baseline for EFficient Fusion-based 3D Occupancy NetworkCode2
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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