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 261270 of 1576 papers

TitleStatusHype
RepVF: A Unified Vector Fields Representation for Multi-task 3D PerceptionCode1
OPEN: Object-wise Position Embedding for Multi-view 3D Object DetectionCode2
FSD-BEV: Foreground Self-Distillation for Multi-view 3D Object DetectionCode1
LabelDistill: Label-guided Cross-modal Knowledge Distillation for Camera-based 3D Object DetectionCode1
Shape2Scene: 3D Scene Representation Learning Through Pre-training on Shape DataCode0
When Pedestrian Detection Meets Multi-Modal Learning: Generalist Model and Benchmark DatasetCode2
Semi-supervised 3D Object Detection with PatchTeacher and PillarMixCode0
Approaching Outside: Scaling Unsupervised 3D Object Detection from 2D SceneCode1
FYI: Flip Your Images for Dataset Distillation0
Exploring Camera Encoder Designs for Autonomous Driving Perception0
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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