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 301–325 of 1576 papers

TitleStatusHype
A Survey of Deep Learning Based Radar and Vision Fusion for 3D Object Detection in Autonomous Driving—0
Fully Test-Time Adaptation for Monocular 3D Object DetectionCode2
Information Entropy Guided Height-aware Histogram for Quantization-friendly Pillar Feature Encoder—0
Is a 3D-Tokenized LLM the Key to Reliable Autonomous Driving?—0
Learning Shared RGB-D Fields: Unified Self-supervised Pre-training for Label-efficient LiDAR-Camera 3D PerceptionCode1
Intent3D: 3D Object Detection in RGB-D Scans Based on Human Intention—0
ContrastAlign: Toward Robust BEV Feature Alignment via Contrastive Learning for Multi-Modal 3D Object Detection—0
Collective Perception Datasets for Autonomous Driving: A Comprehensive Review—0
Hardness-Aware Scene Synthesis for Semi-Supervised 3D Object DetectionCode0
DiffuBox: Refining 3D Object Detection with Point DiffusionCode1
SpotNet: An Image Centric, Lidar Anchored Approach To Long Range Perception—0
UNION: Unsupervised 3D Object Detection using Object Appearance-based Pseudo-ClassesCode1
MonoDETRNext: Next-Generation Accurate and Efficient Monocular 3D Object Detector—0
SE3D: A Framework For Saliency Method Evaluation In 3D ImagingCode0
Drones Help Drones: A Collaborative Framework for Multi-Drone Object Trajectory Prediction and BeyondCode2
TS40K: a 3D Point Cloud Dataset of Rural Terrain and Electrical Transmission System—0
Empowering Urban Traffic Management: Elevated 3D LiDAR for Data Collection and Advanced Object Detection Analysis—0
Mutual Information Analysis in Multimodal Learning Systems—0
FFAM: Feature Factorization Activation Map for Explanation of 3D DetectorsCode0
Multi-View Attentive Contextualization for Multi-View 3D Object Detection—0
FADet: A Multi-sensor 3D Object Detection Network based on Local Featured AttentionCode1
DuoSpaceNet: Leveraging Both Bird's-Eye-View and Perspective View Representations for 3D Object Detection—0
MonoMAE: Enhancing Monocular 3D Detection through Depth-Aware Masked Autoencoders—0
Integrity Monitoring of 3D Object Detection in Automated Driving Systems using Raw Activation Patterns and Spatial Filtering—0
GraphRelate3D: Context-Dependent 3D Object Detection with Inter-Object Relationship Graphs—0
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Benchmark Results

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