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 1041–1050 of 1576 papers

TitleStatusHype
Monocular 3D Object Detection for Autonomous Driving—0
3D Object Detection from a Single Fisheye Image Without a Single Fisheye Training Image—0
Monocular 3D Object Detection using Multi-Stage Approaches with Attention and Slicing aided hyper inference—0
Monocular 3D Object Detection via Feature Domain Adaptation—0
Monocular 3D Object Detection via Geometric Reasoning on Keypoints—0
Monocular 3D Object Detection with Bounding Box Denoising in 3D by Perceiver—0
Monocular 3D Object Detection with Decoupled Structured Polygon Estimation and Height-Guided Depth Estimation—0
Monocular 3D Object Detection with LiDAR Guided Semi Supervised Active Learning—0
Monocular Differentiable Rendering for Self-Supervised 3D Object Detection—0
Monocular Plan View Networks for Autonomous Driving—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