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 731–740 of 1576 papers

TitleStatusHype
QuadBEV: An Efficient Quadruple-Task Perception Framework via Bird's-Eye-View Representation—0
Progressive Multi-Modal Fusion for Robust 3D Object Detection—0
STONE: A Submodular Optimization Framework for Active 3D Object DetectionCode0
Learning 3D Perception from Others' Predictions—0
Panopticus: Omnidirectional 3D Object Detection on Resource-constrained Edge Devices—0
Gaussian-Det: Learning Closed-Surface Gaussians for 3D Object Detection—0
Finetuning Pre-trained Model with Limited Data for LiDAR-based 3D Object Detection by Bridging Domain Gaps—0
Can We Remove the Ground? Obstacle-aware Point Cloud Compression for Remote Object Detection—0
Sparse-to-Dense LiDAR Point Generation by LiDAR-Camera Fusion for 3D Object Detection—0
UniBEVFusion: Unified Radar-Vision BEVFusion for 3D Object Detection—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