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 1111–1120 of 1576 papers

TitleStatusHype
Implicit Surface Contrastive Clustering for LiDAR Point Clouds—0
Clusterformer: Cluster-based Transformer for 3D Object Detection in Point Clouds—0
MetaBEV: Solving Sensor Failures for 3D Detection and Map Segmentation—0
Semi-Supervised Stereo-Based 3D Object Detection via Cross-View Consensus—0
X3KD: Knowledge Distillation Across Modalities, Tasks and Stages for Multi-Camera 3D Object Detection—0
Distilling Focal Knowledge From Imperfect Expert for 3D Object DetectionCode0
Towards Universal LiDAR-Based 3D Object Detection by Multi-Domain Knowledge Transfer—0
ObjectFusion: Multi-modal 3D Object Detection with Object-Centric Fusion—0
Query Refinement Transformer for 3D Instance Segmentation—0
A Simple Vision Transformer for Weakly Semi-supervised 3D Object Detection—0
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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