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 1401–1410 of 1576 papers

TitleStatusHype
RoIFusion: 3D Object Detection from LiDAR and Vision—0
Rooms from Motion: Un-posed Indoor 3D Object Detection as Localization and Mapping—0
Rope3D: The Roadside Perception Dataset for Autonomous Driving and Monocular 3D Object Detection Task—0
Rope3D: TheRoadside Perception Dataset for Autonomous Driving and Monocular 3D Object Detection Task—0
RoPETR: Improving Temporal Camera-Only 3D Detection by Integrating Enhanced Rotary Position Embedding—0
Rotationally Equivariant 3D Object Detection—0
Rotation Matters: Generalized Monocular 3D Object Detection for Various Camera Systems—0
Rotation-robust Intersection over Union for 3D Object Detection—0
RQR3D: Reparametrizing the regression targets for BEV-based 3D object detection—0
RS2AD: End-to-End Autonomous Driving Data Generation from Roadside Sensor Observations—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