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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1101–1150 of 1576 papers

TitleStatusHype
Hashmod: A Hashing Method for Scalable 3D Object Detection—0
HDNET: Exploiting HD Maps for 3D Object Detection—0
HEAD: A Bandwidth-Efficient Cooperative Perception Approach for Heterogeneous Connected and Autonomous Vehicles—0
HeAL3D: Heuristical-enhanced Active Learning for 3D Object Detection—0
HeightFormer: A Semantic Alignment Monocular 3D Object Detection Method from Roadside Perspective—0
HeightFormer: Explicit Height Modeling without Extra Data for Camera-only 3D Object Detection in Bird's Eye View—0
HeightFormer: Learning Height Prediction in Voxel Features for Roadside Vision Centric 3D Object Detection via Transformer—0
Hi-ALPS -- An Experimental Robustness Quantification of Six LiDAR-based Object Detection Systems for Autonomous Driving—0
Hierarchical Cross-Modal Alignment for Open-Vocabulary 3D Object Detection—0
Holistic 3D Scene Understanding From a Single Geo-Tagged Image—0
Homogeneous Multi-modal Feature Fusion and Interaction for 3D Object Detection—0
HVNet: Hybrid Voxel Network for LiDAR Based 3D Object Detection—0
Hyperbolic Cosine Transformer for LiDAR 3D Object Detection—0
HyperDet3D: Learning a Scene-conditioned 3D Object Detector—0
Hyperdimensional Uncertainty Quantification for Multimodal Uncertainty Fusion in Autonomous Vehicles Perception—0
I3DOD: Towards Incremental 3D Object Detection via Prompting—0
IAFA: Instance-aware Feature Aggregation for 3D Object Detection from a Single Image—0
IC-FPS: Instance-Centroid Faster Point Sampling Module for 3D Point-base Object Detection—0
iDet3D: Towards Efficient Interactive Object Detection for LiDAR Point Clouds—0
IDMS: Instance Depth for Multi-scale Monocular 3D Object Detection—0
ImLiDAR: Cross-Sensor Dynamic Message Propagation Network for 3D Object Detection—0
Impact of Video Compression Artifacts on Fisheye Camera Visual Perception Tasks—0
ImpDet: Exploring Implicit Fields for 3D Object Detection—0
Implicit Surface Contrastive Clustering for LiDAR Point Clouds—0
Improved Pillar with Fine-grained Feature for 3D Object Detection—0
Improving 3D Object Detection for Pedestrians with Virtual Multi-View Synthesis Orientation Estimation—0
Improving 3D Object Detection through Progressive Population Based Augmentation—0
epBRM: Improving a Quality of 3D Object Detection using End Point Box Regression Module—0
Improving Distant 3D Object Detection Using 2D Box Supervision—0
Improving LiDAR 3D Object Detection via Range-based Point Cloud Density Optimization—0
Improving Online Lane Graph Extraction by Object-Lane Clustering—0
Improving Point Cloud Semantic Segmentation by Learning 3D Object Detection—0
Improving Robustness of LiDAR-Camera Fusion Model against Weather Corruption from Fusion Strategy Perspective—0
Improving the Intra-class Long-tail in 3D Detection via Rare Example Mining—0
InfoFocus: 3D Object Detection for Autonomous Driving with Dynamic Information Modeling—0
InfraDet3D: Multi-Modal 3D Object Detection based on Roadside Infrastructure Camera and LiDAR Sensors—0
In search of inliers: 3d correspondence by local and global voting—0
Instance-aware Multi-Camera 3D Object Detection with Structural Priors Mining and Self-Boosting Learning—0
InstanceBEV: Unifying Instance and BEV Representation for Global Modeling—0
Integrity Monitoring of 3D Object Detection in Automated Driving Systems using Raw Activation Patterns and Spatial Filtering—0
Intent3D: 3D Object Detection in RGB-D Scans Based on Human Intention—0
IPOD: Intensive Point-based Object Detector for Point Cloud—0
IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain—0
Is a 3D-Tokenized LLM the Key to Reliable Autonomous Driving?—0
Ithaca365: Dataset and Driving Perception under Repeated and Challenging Weather Conditions—0
It's All Around You: Range-Guided Cylindrical Network for 3D Object Detection—0
Joint 3D Instance Segmentation and Object Detection for Autonomous Driving—0
Joint 3D Object Detection and Tracking Using Spatio-Temporal Representation of Camera Image and LiDAR Point Clouds—0
Joint object detection and re-identification for 3D obstacle multi-camera systems—0
Just Add $100 More: Augmenting NeRF-based Pseudo-LiDAR Point Cloud for Resolving Class-imbalance Problem—0
Show:102550
← PrevPage 23 of 32Next →
All datasetsnuScenesScanNetV2SUN-RGBD valKITTI Cars EasyKITTI Cars HardnuScenes Camera OnlyKITTI Cars Easy valKITTI Cars Moderate valnuscenes Camera-RadarView-of-Delft (val)KITTI Cars Hard valDAIR-V2X-I

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