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 611–620 of 1576 papers

TitleStatusHype
Rooms from Motion: Un-posed Indoor 3D Object Detection as Localization and Mapping—0
The Meeseeks Mesh: Spatially Consistent 3D Adversarial Objects for BEV Detector—0
RQR3D: Reparametrizing the regression targets for BEV-based 3D object detection—0
CodeMerge: Codebook-Guided Model Merging for Robust Test-Time Adaptation in Autonomous Driving—0
InstanceBEV: Unifying Instance and BEV Representation for Global Modeling—0
MoRAL: Motion-aware Multi-Frame 4D Radar and LiDAR Fusion for Robust 3D Object Detection—0
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection—0
PillarMamba: Learning Local-Global Context for Roadside Point Cloud via Hybrid State Space Model—0
MonoCoP: Chain-of-Prediction for Monocular 3D Object Detection—0
Efficient On-Chip Implementation of 4D Radar-Based 3D Object Detection on Hailo-8L—0
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All datasetsnuScenesScanNetV2SUN-RGBD valKITTI Cars EasyKITTI Cars HardnuScenes Camera OnlyKITTI Cars Easy valKITTI Cars Moderate valnuscenes Camera-RadarView-of-Delft (val)KITTI Cars Hard valDAIR-V2X-I

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