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 391400 of 1576 papers

TitleStatusHype
DID-M3D: Decoupling Instance Depth for Monocular 3D Object DetectionCode1
Teachers in concordance for pseudo-labeling of 3D sequential dataCode1
Physical Attack on Monocular Depth Estimation with Optimal Adversarial PatchesCode1
Mix-Teaching: A Simple, Unified and Effective Semi-Supervised Learning Framework for Monocular 3D Object DetectionCode1
Bounding Box Disparity: 3D Metrics for Object Detection With Full Degree of FreedomCode1
GLENet: Boosting 3D Object Detectors with Generative Label Uncertainty EstimationCode1
Masked Autoencoder for Self-Supervised Pre-training on Lidar Point CloudsCode1
PolarFormer: Multi-camera 3D Object Detection with Polar TransformerCode1
HRFuser: A Multi-resolution Sensor Fusion Architecture for 2D Object DetectionCode1
Color-aware two-branch DCNN for efficient plant disease classificationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1EA-LSSNDS0.78Unverified
2MegFusionNDS0.77Unverified
3MMFusion-eNDS0.77Unverified
4BEVFusion-eNDS0.76Unverified
5RacoonPowerNDS0.76Unverified
6DeepInteraction-largeNDS0.76Unverified
7DeepInteraction-eNDS0.76Unverified
8FusionVPENDS0.75Unverified
9FocalFormer3D-FNDS0.75Unverified
10CenterPoint-FusionNDS0.75Unverified