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 801–810 of 1576 papers

TitleStatusHype
CTS: Sim-to-Real Unsupervised Domain Adaptation on 3D Detection—0
MDHA: Multi-Scale Deformable Transformer with Hybrid Anchors for Multi-View 3D Object DetectionCode0
Towards Open-set Camera 3D Object Detection—0
DPO: Dual-Perturbation Optimization for Test-time Adaptation in 3D Object DetectionCode0
Syn-to-Real Unsupervised Domain Adaptation for Indoor 3D Object DetectionCode0
Multi-Dimensional Pruning: Joint Channel, Layer and Block Pruning with Latency Constraint—0
Enhancing Generalizability of Representation Learning for Data-Efficient 3D Scene Understanding—0
Semi-Supervised Domain Adaptation Using Target-Oriented Domain Augmentation for 3D Object DetectionCode0
SparseDet: A Simple and Effective Framework for Fully Sparse LiDAR-based 3D Object Detection—0
Shelf-Supervised Cross-Modal Pre-Training for 3D Object DetectionCode0
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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