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

Showing 401410 of 1576 papers

TitleStatusHype
Multimodal Transformer for Automatic 3D Annotation and Object DetectionCode1
MonoNeRD: NeRF-like Representations for Monocular 3D Object DetectionCode1
ALPI: Auto-Labeller with Proxy Injection for 3D Object Detection using 2D Labels OnlyCode1
DI-V2X: Learning Domain-Invariant Representation for Vehicle-Infrastructure Collaborative 3D Object DetectionCode1
Learning Auxiliary Monocular Contexts Helps Monocular 3D Object DetectionCode1
Divide and Conquer: 3D Point Cloud Instance Segmentation With Point-Wise BinarizationCode1
3DPPE: 3D Point Positional Encoding for Transformer-based Multi-Camera 3D Object DetectionCode1
3D Bounding Box Estimation Using Deep Learning and GeometryCode1
Bootstraping Clustering of Gaussians for View-consistent 3D Scene UnderstandingCode1
MonoLSS: Learnable Sample Selection For Monocular 3D DetectionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1EA-LSSNDS0.78Unverified
2MMFusion-eNDS0.77Unverified
3MegFusionNDS0.77Unverified
4RacoonPowerNDS0.76Unverified
5BEVFusion-eNDS0.76Unverified
6DeepInteraction-largeNDS0.76Unverified
7DeepInteraction-eNDS0.76Unverified
8DAANDS0.75Unverified
9FusionVPENDS0.75Unverified
10CenterPoint-FusionNDS0.75Unverified