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 761770 of 1576 papers

TitleStatusHype
MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object LocalizationCode0
Monocular 3D Object Detection with Pseudo-LiDAR Point CloudCode0
KAN-RCBEVDepth: A multi-modal fusion algorithm in object detection for autonomous drivingCode0
Monocular 2D Camera-based Proximity Monitoring for Human-Machine Collision Warning on Construction SitesCode0
Monocular 3D Object Detection Leveraging Accurate Proposals and Shape ReconstructionCode0
Frustum ConvNet: Sliding Frustums to Aggregate Local Point-Wise Features for Amodal 3D Object DetectionCode0
MLVSNet: Multi-Level Voting Siamese Network for 3D Visual TrackingCode0
M&M3D: Multi-Dataset Training and Efficient Network for Multi-view 3D Object DetectionCode0
Focal Loss in 3D Object DetectionCode0
FM-OV3D: Foundation Model-based Cross-modal Knowledge Blending for Open-Vocabulary 3D DetectionCode0
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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