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 601–650 of 1576 papers

TitleStatusHype
Group-Free 3D Object Detection via TransformersCode1
FastOcc: Accelerating 3D Occupancy Prediction by Fusing the 2D Bird's-Eye View and Perspective View—0
CMDA: Cross-Modal and Domain Adversarial Adaptation for LiDAR-Based 3D Object Detection—0
A 3D Object Detection and Pose Estimation Pipeline Using RGB-D Images—0
False Positive Sampling-based Data Augmentation for Enhanced 3D Object Detection Accuracy—0
ClusterFusion: Leveraging Radar Spatial Features for Radar-Camera 3D Object Detection in Autonomous Vehicles—0
FALO: Fast and Accurate LiDAR 3D Object Detection on Resource-Constrained Devices—0
Falling Things: A Synthetic Dataset for 3D Object Detection and Pose Estimation—0
Clusterformer: Cluster-based Transformer for 3D Object Detection in Point Clouds—0
3D Object Detection and High-Resolution Traffic Parameters Extraction Using Low-Resolution LiDAR Data—0
Exploring the Capabilities and Limits of 3D Monocular Object Detection -- A Study on Simulation and Real World Data—0
Exploring Geometry-Aware Contrast and Clustering Harmonization for Self-Supervised 3D Object Detection—0
Clouds of Oriented Gradients for 3D Detection of Objects, Surfaces, and Indoor Scene Layouts—0
Exploring Domain Shift on Radar-Based 3D Object Detection Amidst Diverse Environmental Conditions—0
CLIP-BEVFormer: Enhancing Multi-View Image-Based BEV Detector with Ground Truth Flow—0
CleverDistiller: Simple and Spatially Consistent Cross-modal Distillation—0
Exploring Camera Encoder Designs for Autonomous Driving Perception—0
Exploring Adversarial Robustness of LiDAR-Camera Fusion Model in Autonomous Driving—0
3D Object Detection and Instance Segmentation from 3D Range and 2D Color Images—0
Exploring 2D Data Augmentation for 3D Monocular Object Detection—0
A Review of 3D Object Detection with Vision-Language Models—0
Class-Aware PillarMix: Can Mixed Sample Data Augmentation Enhance 3D Object Detection with Radar Point Clouds?—0
Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection—0
3M3D: Multi-view, Multi-path, Multi-representation for 3D Object Detection—0
Weakly Supervised 3D Object Detection with Multi-Stage Generalization—0
Explicit3D: Graph Network with Spatial Inference for Single Image 3D Object Detection—0
Explaining the Ambiguity of Object Detection and 6D Pose From Visual Data—0
Explainable Multi-Camera 3D Object Detection with Transformer-Based Saliency Maps—0
Expandable YOLO: 3D Object Detection from RGB-D Images—0
Cirrus: A Long-range Bi-pattern LiDAR Dataset—0
EVT: Efficient View Transformation for Multi-Modal 3D Object Detection—0
Every View Counts: Cross-View Consistency in 3D Object Detection with Hybrid-Cylindrical-Spherical Voxelization—0
Every Dataset Counts: Scaling up Monocular 3D Object Detection with Joint Datasets Training—0
Evaluating the Impact of Synthetic Data on Object Detection Tasks in Autonomous Driving—0
CenterRadarNet: Joint 3D Object Detection and Tracking Framework using 4D FMCW Radar—0
Equivariant Spatio-Temporal Self-Supervision for LiDAR Object Detection—0
A Point-Based Approach to Efficient LiDAR Multi-Task Perception—0
Learning Monocular 3D Vehicle Detection without 3D Bounding Box Labels—0
Learning Temporal Cues by Predicting Objects Move for Multi-camera 3D Object Detection—0
Center Feature Fusion: Selective Multi-Sensor Fusion of Center-based Objects—0
AOP-Net: All-in-One Perception Network for Joint LiDAR-based 3D Object Detection and Panoptic Segmentation—0
Anyview: Generalizable Indoor 3D Object Detection with Variable Frames—0
Enhancing Generalizability of Representation Learning for Data-Efficient 3D Scene Understanding—0
Center3D: Center-based Monocular 3D Object Detection with Joint Depth Understanding—0
3D-VField: Adversarial Augmentation of Point Clouds for Domain Generalization in 3D Object Detection—0
Multi-View Representation is What You Need for Point-Cloud Pre-Training—0
Enhancing 3D Object Detection in Autonomous Vehicles Based on Synthetic Virtual Environment Analysis—0
Enhanced K-Radar: Optimal Density Reduction to Improve Detection Performance and Accessibility of 4D Radar Tensor-based Object Detection—0
CatFree3D: Category-agnostic 3D Object Detection with Diffusion—0
Anytime-Lidar: Deadline-aware 3D Object Detection—0
Show:102550
← PrevPage 13 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