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 1081–1090 of 1576 papers

TitleStatusHype
Efficient Transformer-based 3D Object Detection with Dynamic Token Halting—0
LoGoNet: Towards Accurate 3D Object Detection with Local-to-Global Cross-Modal FusionCode0
X^3KD: Knowledge Distillation Across Modalities, Tasks and Stages for Multi-Camera 3D Object Detection—0
Towards Domain Generalization for Multi-view 3D Object Detection in Bird-Eye-View—0
Nearest Neighbors Meet Deep Neural Networks for Point Cloud Analysis—0
AdaptiveShape: Solving Shape Variability for 3D Object Detection with Geometry Aware Anchor Distributions—0
DuEqNet: Dual-Equivariance Network in Outdoor 3D Object Detection for Autonomous Driving—0
Introducing Depth into Transformer-based 3D Object Detection—0
Transformer-Based Sensor Fusion for Autonomous Driving: A SurveyCode0
A Flexible Multi-view Multi-modal Imaging System for Outdoor Scenes—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