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 101110 of 1576 papers

TitleStatusHype
MonoCD: Monocular 3D Object Detection with Complementary DepthsCode2
Monocular 3D Object Detection with Depth from MotionCode2
Multi-Class Road User Detection With 3+1D Radar in the View-of-Delft DatasetCode2
MultiCorrupt: A Multi-Modal Robustness Dataset and Benchmark of LiDAR-Camera Fusion for 3D Object DetectionCode2
NeRF-MAE: Masked AutoEncoders for Self-Supervised 3D Representation Learning for Neural Radiance FieldsCode2
nuScenes: A multimodal dataset for autonomous drivingCode2
CenterFormer: Center-based Transformer for 3D Object DetectionCode2
UniScene: Multi-Camera Unified Pre-training via 3D Scene Reconstruction for Autonomous DrivingCode2
Center-based 3D Object Detection and TrackingCode2
Aria Digital Twin: A New Benchmark Dataset for Egocentric 3D Machine PerceptionCode2
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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