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 151160 of 1576 papers

TitleStatusHype
Image-to-Lidar Self-Supervised Distillation for Autonomous Driving DataCode2
MambaFusion: Height-Fidelity Dense Global Fusion for Multi-modal 3D Object DetectionCode2
MIM4D: Masked Modeling with Multi-View Video for Autonomous Driving Representation LearningCode2
MixSup: Mixed-grained Supervision for Label-efficient LiDAR-based 3D Object DetectionCode2
nuScenes: A multimodal dataset for autonomous drivingCode2
ARM3D: Attention-based relation module for indoor 3D object detectionCode1
ARKitScenes: A Diverse Real-World Dataset For 3D Indoor Scene Understanding Using Mobile RGB-D DataCode1
Diffusion-SS3D: Diffusion Model for Semi-supervised 3D Object DetectionCode1
DiffuBox: Refining 3D Object Detection with Point DiffusionCode1
Disentangling 3D Prototypical Networks For Few-Shot Concept LearningCode1
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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