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

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Showing 851–860 of 1576 papers

TitleStatusHype
Run-time Monitoring of 3D Object Detection in Automated Driving Systems Using Early Layer Neural Activation Patterns—0
SparseAD: Sparse Query-Centric Paradigm for Efficient End-to-End Autonomous Driving—0
Sparse Points to Dense Clouds: Enhancing 3D Detection with Limited LiDAR Data—0
Label-Efficient 3D Object Detection For Road-Side Units—0
MOSE: Boosting Vision-based Roadside 3D Object Detection with Scene Cues—0
DifFUSER: Diffusion Model for Robust Multi-Sensor Fusion in 3D Object Detection and BEV Segmentation—0
Learning Temporal Cues by Predicting Objects Move for Multi-camera 3D Object Detection—0
Weak-to-Strong 3D Object Detection with X-Ray DistillationCode0
Accurate Cutting-point Estimation for Robotic Lychee Harvesting through Geometry-aware Learning—0
CRKD: Enhanced Camera-Radar Object Detection with Cross-modality Knowledge Distillation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1EA-LSSNDS0.78—Unverified
2MMFusion-eNDS0.77—Unverified
3MegFusionNDS0.77—Unverified
4RacoonPowerNDS0.76—Unverified
5BEVFusion-eNDS0.76—Unverified
6DeepInteraction-largeNDS0.76—Unverified
7DeepInteraction-eNDS0.76—Unverified
8DAANDS0.75—Unverified
9FusionVPENDS0.75—Unverified
10CenterPoint-FusionNDS0.75—Unverified