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 276–300 of 1576 papers

TitleStatusHype
Advancing Self-supervised Monocular Depth Learning with Sparse LiDARCode1
Fusing Event-based and RGB camera for Robust Object Detection in Adverse ConditionsCode1
Geometry-based Distance Decomposition for Monocular 3D Object DetectionCode1
BEVDistill: Cross-Modal BEV Distillation for Multi-View 3D Object DetectionCode1
FrustumFormer: Adaptive Instance-aware Resampling for Multi-view 3D DetectionCode1
From Multi-View to Hollow-3D: Hallucinated Hollow-3D R-CNN for 3D Object DetectionCode1
From Voxel to Point: IoU-guided 3D Object Detection for Point Cloud with Voxel-to-Point DecoderCode1
Frustum PointNets for 3D Object Detection from RGB-D DataCode1
A Dual-Cycled Cross-View Transformer Network for Unified Road Layout Estimation and 3D Object Detection in the Bird's-Eye-ViewCode1
Better Monocular 3D Detectors with LiDAR from the PastCode1
AD-L-JEPA: Self-Supervised Spatial World Models with Joint Embedding Predictive Architecture for Autonomous Driving with LiDAR DataCode1
Fooling LiDAR Perception via Adversarial Trajectory PerturbationCode1
Frustum-PointPillars: A Multi-Stage Approach for 3D Object Detection using RGB Camera and LiDARCode1
Benchmarking the Robustness of LiDAR-Camera Fusion for 3D Object DetectionCode1
Benchmarking Robustness of 3D Object Detection to Common CorruptionsCode1
Flow-Based Feature Fusion for Vehicle-Infrastructure Cooperative 3D Object DetectionCode1
Behind the Curtain: Learning Occluded Shapes for 3D Object DetectionCode1
Find n' Propagate: Open-Vocabulary 3D Object Detection in Urban EnvironmentsCode1
Fine-Grained Pillar Feature Encoding Via Spatio-Temporal Virtual Grid for 3D Object DetectionCode1
Back-tracing Representative Points for Voting-based 3D Object Detection in Point CloudsCode1
CubeSLAM: Monocular 3D Object SLAMCode1
Fog Simulation on Real LiDAR Point Clouds for 3D Object Detection in Adverse WeatherCode1
FSD-BEV: Foreground Self-Distillation for Multi-view 3D Object DetectionCode1
Geometry Uncertainty Projection Network for Monocular 3D Object DetectionCode1
Back to Reality: Weakly-supervised 3D Object Detection with Shape-guided Label EnhancementCode1
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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