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 551–575 of 1576 papers

TitleStatusHype
Find n' Propagate: Open-Vocabulary 3D Object Detection in Urban EnvironmentsCode1
Finding Your (3D) Center: 3D Object Detection Using a Learned LossCode1
CoBEV: Elevating Roadside 3D Object Detection with Depth and Height ComplementarityCode1
FGR: Frustum-Aware Geometric Reasoning for Weakly Supervised 3D Vehicle DetectionCode1
Accelerate 3D Object Detection Models via Zero-Shot Attention Key PruningCode1
Fusing Event-based and RGB camera for Robust Object Detection in Adverse ConditionsCode1
Lite-FPN for Keypoint-based Monocular 3D Object DetectionCode1
Fusion is Not Enough: Single Modal Attacks on Fusion Models for 3D Object DetectionCode1
InScope: A New Real-world 3D Infrastructure-side Collaborative Perception Dataset for Open Traffic ScenariosCode1
itKD: Interchange Transfer-based Knowledge Distillation for 3D Object DetectionCode1
Geometry Uncertainty Projection Network for Monocular 3D Object DetectionCode1
GLENet: Boosting 3D Object Detectors with Generative Label Uncertainty EstimationCode1
Attention-based Proposals Refinement for 3D Object DetectionCode1
FGFusion: Fine-Grained Lidar-Camera Fusion for 3D Object DetectionCode1
CN-RMA: Combined Network with Ray Marching Aggregation for 3D Indoor Object Detection from Multi-view ImagesCode1
MASS: Multi-Attentional Semantic Segmentation of LiDAR Data for Dense Top-View UnderstandingCode1
Improving 3D Object Detection with Channel-wise TransformerCode1
A Simple and Efficient Multi-task Network for 3D Object Detection and Road UnderstandingCode1
Mix-Teaching: A Simple, Unified and Effective Semi-Supervised Learning Framework for Monocular 3D Object DetectionCode1
MLCVNet: Multi-Level Context VoteNet for 3D Object DetectionCode1
CN-RMA: Combined Network with Ray Marching Aggregation for 3D Indoors Object Detection from Multi-view ImagesCode1
Investigating the Impact of Multi-LiDAR Placement on Object Detection for Autonomous DrivingCode1
FCOS3D: Fully Convolutional One-Stage Monocular 3D Object DetectionCode1
3D Dual-Fusion: Dual-Domain Dual-Query Camera-LiDAR Fusion for 3D Object DetectionCode1
GUPNet++: Geometry Uncertainty Propagation Network for Monocular 3D Object DetectionCode1
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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