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 251–300 of 1576 papers

TitleStatusHype
Enhancing 3D Object Detection with 2D Detection-Guided Query AnchorsCode1
Learning Class Prototypes for Unified Sparse Supervised 3D Object DetectionCode1
ARM3D: Attention-based relation module for indoor 3D object detectionCode1
Learning for Vehicle-to-Vehicle Cooperative Perception under Lossy CommunicationCode1
Learning High-resolution Vector Representation from Multi-Camera Images for 3D Object DetectionCode1
Lidar Light Scattering Augmentation (LISA): Physics-based Simulation of Adverse Weather Conditions for 3D Object DetectionCode1
M3DeTR: Multi-representation, Multi-scale, Mutual-relation 3D Object Detection with TransformersCode1
itKD: Interchange Transfer-based Knowledge Distillation for 3D Object DetectionCode1
3D Object Detection with PointformerCode1
Is Pseudo-Lidar needed for Monocular 3D Object detection?Code1
Kinematic 3D Object Detection in Monocular VideoCode1
SimDistill: Simulated Multi-modal Distillation for BEV 3D Object DetectionCode1
Efficient Feature Aggregation and Scale-Aware Regression for Monocular 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
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
AeDet: Azimuth-invariant Multi-view 3D Object DetectionCode1
DynOPETs: A Versatile Benchmark for Dynamic Object Pose Estimation and Tracking in Moving Camera ScenariosCode1
Advancing Self-supervised Monocular Depth Learning with Sparse LiDARCode1
EarlyBird: Early-Fusion for Multi-View Tracking in the Bird's Eye ViewCode1
BEVDistill: Cross-Modal BEV Distillation for Multi-View 3D Object DetectionCode1
DualDiff: Dual-branch Diffusion Model for Autonomous Driving with Semantic FusionCode1
DSRC: Learning Density-insensitive and Semantic-aware Collaborative Representation against CorruptionsCode1
DualDiff+: Dual-Branch Diffusion for High-Fidelity Video Generation with Reward GuidanceCode1
Investigating the Impact of Multi-LiDAR Placement on Object Detection for Autonomous DrivingCode1
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
Dual Radar: A Multi-modal Dataset with Dual 4D Radar for Autonomous DrivingCode1
ImVoteNet: Boosting 3D Object Detection in Point Clouds with Image VotesCode1
Benchmarking the Robustness of LiDAR-Camera Fusion for 3D Object DetectionCode1
Benchmarking Robustness of 3D Object Detection to Common CorruptionsCode1
DSGN: Deep Stereo Geometry Network for 3D Object DetectionCode1
DSGN++: Exploiting Visual-Spatial Relation for Stereo-based 3D DetectorsCode1
Behind the Curtain: Learning Occluded Shapes for 3D Object DetectionCode1
ImGeoNet: Image-induced Geometry-aware Voxel Representation for Multi-view 3D Object DetectionCode1
3D Small Object Detection with Dynamic Spatial PruningCode1
End-To-End Optimization of LiDAR Beam Configuration for 3D Object Detection and LocalizationCode1
Back-tracing Representative Points for Voting-based 3D Object Detection in Point CloudsCode1
Improving 3D Object Detection with Channel-wise TransformerCode1
InScope: A New Real-world 3D Infrastructure-side Collaborative Perception Dataset for Open Traffic ScenariosCode1
labelCloud: A Lightweight Domain-Independent Labeling Tool for 3D Object Detection in Point CloudsCode1
Back to Reality: Weakly-supervised 3D Object Detection with Shape-guided Label EnhancementCode1
Homography Loss for Monocular 3D Object DetectionCode1
HoughNet: Integrating near and long-range evidence for visual detectionCode1
AYDIV: Adaptable Yielding 3D Object Detection via Integrated Contextual Vision TransformerCode1
Holistic 3D Scene Understanding from a Single Image with Implicit RepresentationCode1
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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