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 991–1000 of 1576 papers

TitleStatusHype
Group Regression for Query Based Object Detection and Tracking—0
I3DOD: Towards Incremental 3D Object Detection via Prompting—0
On Offline Evaluation of 3D Object Detection for Autonomous Driving—0
Perspective-aware Convolution for Monocular 3D Object DetectionCode0
Advancements in Point Cloud Data Augmentation for Deep Learning: A Survey—0
QD-BEV : Quantization-aware View-guided Distillation for Multi-view 3D Object Detection—0
ThermRad: A Multi-modal Dataset for Robust 3D Object Detection under Challenging Conditions—0
Representation Disparity-aware Distillation for 3D Object Detection—0
PatchContrast: Self-Supervised Pre-training for 3D Object Detection—0
UniWorld: Autonomous Driving Pre-training via World ModelsCode0
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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