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 181190 of 1576 papers

TitleStatusHype
DSRC: Learning Density-insensitive and Semantic-aware Collaborative Representation against CorruptionsCode1
PointCFormer: a Relation-based Progressive Feature Extraction Network for Point Cloud CompletionCode1
Towards Flexible 3D Perception: Object-Centric Occupancy Completion Augments 3D Object DetectionCode1
Bootstraping Clustering of Gaussians for View-consistent 3D Scene UnderstandingCode1
LSSInst: Improving Geometric Modeling in LSS-Based BEV Perception with Instance RepresentationCode1
Efficient Feature Aggregation and Scale-Aware Regression for Monocular 3D Object DetectionCode1
CRT-Fusion: Camera, Radar, Temporal Fusion Using Motion Information for 3D Object DetectionCode1
MVSDet: Multi-View Indoor 3D Object Detection via Efficient Plane SweepsCode1
Real-time Stereo-based 3D Object Detection for Streaming PerceptionCode1
TEOcc: Radar-camera Multi-modal Occupancy Prediction via Temporal EnhancementCode1
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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