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 821830 of 1576 papers

TitleStatusHype
DETR4D: Direct Multi-View 3D Object Detection with Sparse Attention0
MAELi: Masked Autoencoder for Large-Scale LiDAR Point Clouds0
ConQueR: Query Contrast Voxel-DETR for 3D Object DetectionCode1
VINet: Lightweight, Scalable, and Heterogeneous Cooperative Perception for 3D Object Detection0
MegaPose: 6D Pose Estimation of Novel Objects via Render & CompareCode2
BEV-MAE: Bird's Eye View Masked Autoencoders for Point Cloud Pre-training in Autonomous Driving ScenariosCode1
Focal-PETR: Embracing Foreground for Efficient Multi-Camera 3D Object Detection0
Multi-Sem Fusion: Multimodal Semantic Fusion for 3D Object Detection0
SemanticBEVFusion: Rethink LiDAR-Camera Fusion in Unified Bird's-Eye View Representation for 3D Object Detection0
Towards Accurate Ground Plane Normal Estimation from Ego-MotionCode1
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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