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 711720 of 1576 papers

TitleStatusHype
SimDistill: Simulated Multi-modal Distillation for BEV 3D Object DetectionCode1
LinK: Linear Kernel for LiDAR-based 3D PerceptionCode1
Unsupervised Adaptation from Repeated Traversals for Autonomous DrivingCode0
UniDistill: A Universal Cross-Modality Knowledge Distillation Framework for 3D Object Detection in Bird's-Eye ViewCode1
Learning to Zoom and Unzoom0
Viewpoint Equivariance for Multi-View 3D Object DetectionCode1
BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown ObjectsCode3
MoGDE: Boosting Mobile Monocular 3D Object Detection with Ground Depth Estimation0
MonoATT: Online Monocular 3D Object Detection with Adaptive Token Transformer0
MV-JAR: Masked Voxel Jigsaw and Reconstruction for LiDAR-Based Self-Supervised Pre-TrainingCode1
Show:102550
← PrevPage 72 of 158Next →

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