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 1281–1290 of 1576 papers

TitleStatusHype
Static-Dynamic Co-Teaching for Class-Incremental 3D Object Detection—0
STD: Sparse-to-Dense 3D Object Detector for Point Cloud—0
Stereo CenterNet based 3D Object Detection for Autonomous Driving—0
StereoDistill: Pick the Cream from LiDAR for Distilling Stereo-based 3D Object Detection—0
Stereo Frustums: A Siamese Pipeline for 3D Object Detection—0
Stereo Object Matching Network—0
Stereo RGB and Deeper LIDAR Based Network for 3D Object Detection—0
Structure Aware and Class Balanced 3D Object Detection on nuScenes Dataset—0
Structure Information is the Key: Self-Attention RoI Feature Extractor in 3D Object Detection—0
STS: Surround-view Temporal Stereo for Multi-view 3D Detection—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