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 741750 of 1576 papers

TitleStatusHype
BEVHeight: A Robust Framework for Vision-based Roadside 3D Object DetectionCode2
V2V4Real: A Real-world Large-scale Dataset for Vehicle-to-Vehicle Cooperative PerceptionCode2
PiMAE: Point Cloud and Image Interactive Masked Autoencoders for 3D Object DetectionCode1
Uni3D: A Unified Baseline for Multi-dataset 3D Object Detection0
Enhanced K-Radar: Optimal Density Reduction to Improve Detection Performance and Accessibility of 4D Radar Tensor-based Object Detection0
ReBound: An Open-Source 3D Bounding Box Annotation Tool for Active LearningCode1
Bi3D: Bi-domain Active Learning for Cross-domain 3D Object Detection0
Efficient Transformer-based 3D Object Detection with Dynamic Token Halting0
DDS3D: Dense Pseudo-Labels with Dynamic Threshold for Semi-Supervised 3D Object DetectionCode1
Calibration-free BEV Representation for Infrastructure PerceptionCode1
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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