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 631640 of 1576 papers

TitleStatusHype
Frame Fusion with Vehicle Motion Prediction for 3D Object Detection0
Predict to Detect: Prediction-guided 3D Object Detection using Sequential ImagesCode1
Towards a Robust Sensor Fusion Step for 3D Object Detection on Corrupted DataCode0
Aria Digital Twin: A New Benchmark Dataset for Egocentric 3D Machine PerceptionCode2
Improving LiDAR 3D Object Detection via Range-based Point Cloud Density Optimization0
DetZero: Rethinking Offboard 3D Object Detection with Long-term Sequential Point CloudsCode2
Point-LGMask: Local and Global Contexts Embedding for Point Cloud Pre-training with Multi-Ratio MaskingCode0
Weakly Supervised 3D Object Detection with Multi-Stage Generalization0
MoDAR: Using Motion Forecasting for 3D Object Detection in Point Cloud SequencesCode1
Multi-View Representation is What You Need for Point-Cloud Pre-Training0
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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