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 251–275 of 1576 papers

TitleStatusHype
Beyond One Shot, Beyond One Perspective: Cross-View and Long-Horizon Distillation for Better LiDAR RepresentationsCode1
Kinematic 3D Object Detection in Monocular VideoCode1
ARM3D: Attention-based relation module for indoor 3D object detectionCode1
CoreNet: Conflict Resolution Network for Point-Pixel Misalignment and Sub-Task Suppression of 3D LiDAR-Camera Object DetectionCode1
From Voxel to Point: IoU-guided 3D Object Detection for Point Cloud with Voxel-to-Point DecoderCode1
Fusing Event-based and RGB camera for Robust Object Detection in Adverse ConditionsCode1
GO-N3RDet: Geometry Optimized NeRF-enhanced 3D Object DetectorCode1
Learning Ego 3D Representation as Ray TracingCode1
FGFusion: Fine-Grained Lidar-Camera Fusion for 3D Object DetectionCode1
FGR: Frustum-Aware Geometric Reasoning for Weakly Supervised 3D Vehicle DetectionCode1
3D Object Detection with PointformerCode1
FCOS3D: Fully Convolutional One-Stage Monocular 3D Object DetectionCode1
Finding Your (3D) Center: 3D Object Detection Using a Learned LossCode1
SimDistill: Simulated Multi-modal Distillation for BEV 3D Object DetectionCode1
Faraway-Frustum: Dealing with Lidar Sparsity for 3D Object Detection using FusionCode1
FASTer: Focal Token Acquiring-and-Scaling Transformer for Long-term 3D Object DetectionCode1
BEVNeXt: Reviving Dense BEV Frameworks for 3D Object DetectionCode1
BEV-MAE: Bird's Eye View Masked Autoencoders for Point Cloud Pre-training in Autonomous Driving ScenariosCode1
AFDet: Anchor Free One Stage 3D Object DetectionCode1
FastPillars: A Deployment-friendly Pillar-based 3D DetectorCode1
Find n' Propagate: Open-Vocabulary 3D Object Detection in Urban EnvironmentsCode1
BEV-LGKD: A Unified LiDAR-Guided Knowledge Distillation Framework for BEV 3D Object DetectionCode1
A Fast Unified System for 3D Object Detection and TrackingCode1
3D Object Detection with a Self-supervised Lidar Scene Flow BackboneCode1
FADet: A Multi-sensor 3D Object Detection Network based on Local Featured AttentionCode1
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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