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 1401–1450 of 1576 papers

TitleStatusHype
RoIFusion: 3D Object Detection from LiDAR and Vision—0
Rooms from Motion: Un-posed Indoor 3D Object Detection as Localization and Mapping—0
Rope3D: The Roadside Perception Dataset for Autonomous Driving and Monocular 3D Object Detection Task—0
Rope3D: TheRoadside Perception Dataset for Autonomous Driving and Monocular 3D Object Detection Task—0
RoPETR: Improving Temporal Camera-Only 3D Detection by Integrating Enhanced Rotary Position Embedding—0
Rotationally Equivariant 3D Object Detection—0
Rotation Matters: Generalized Monocular 3D Object Detection for Various Camera Systems—0
Rotation-robust Intersection over Union for 3D Object Detection—0
RQR3D: Reparametrizing the regression targets for BEV-based 3D object detection—0
RS2AD: End-to-End Autonomous Driving Data Generation from Roadside Sensor Observations—0
RS-DFM: A Remote Sensing Distributed Foundation Model for Diverse Downstream Tasks—0
RSN: Range Sparse Net for Efficient, Accurate LiDAR 3D Object Detection—0
RTNH+: Enhanced 4D Radar Object Detection Network using Combined CFAR-based Two-level Preprocessing and Vertical Encoding—0
Run-time Monitoring of 3D Object Detection in Automated Driving Systems Using Early Layer Neural Activation Patterns—0
RV-FuseNet: Range View Based Fusion of Time-Series LiDAR Data for Joint 3D Object Detection and Motion Forecasting—0
S2R-ViT for Multi-Agent Cooperative Perception: Bridging the Gap from Simulation to Reality—0
S3PT: Scene Semantics and Structure Guided Clustering to Boost Self-Supervised Pre-Training for Autonomous Driving—0
Safety-Aware Hardening of 3D Object Detection Neural Network Systems—0
SAM-Guided Masked Token Prediction for 3D Scene Understanding—0
Sample, Crop, Track: Self-Supervised Mobile 3D Object Detection for Urban Driving LiDAR—0
Scalable Primitives for Generalized Sensor Fusion in Autonomous Vehicles—0
Scan2Cap: Context-aware Dense Captioning in RGB-D Scans—0
Scatter Points in Space: 3D Detection from Multi-view Monocular Images—0
SceneScript: Reconstructing Scenes With An Autoregressive Structured Language Model—0
Scene Understanding Networks for Autonomous Driving based on Around View Monitoring System—0
SCP: Scene Completion Pre-training for 3D Object Detection—0
SDGE: Stereo Guided Depth Estimation for 360^ Camera Sets—0
SDVRF: Sparse-to-Dense Voxel Region Fusion for Multi-modal 3D Object Detection—0
SEFormer: Structure Embedding Transformer for 3D Object Detection—0
Selectively Dilated Convolution for Accuracy-Preserving Sparse Pillar-based Embedded 3D Object Detection—0
Self-Supervised 3D Monocular Object Detection by Recycling Bounding Boxes—0
Self-supervised 3D Object Detection from Monocular Pseudo-LiDAR—0
Self-supervised cross-modality learning for uncertainty-aware object detection and recognition in applications which lack pre-labelled training data—0
Self-Supervised Pre-training with Combined Datasets for 3D Perception in Autonomous Driving—0
SemanticBEVFusion: Rethink LiDAR-Camera Fusion in Unified Bird's-Eye View Representation for 3D Object Detection—0
Semantics-aware LiDAR-Only Pseudo Point Cloud Generation for 3D Object Detection—0
Semantic-Supervised Spatial-Temporal Fusion for LiDAR-based 3D Object Detection—0
Semi-supervised 3D Object Detection via Adaptive Pseudo-Labeling—0
Semi-supervised 3D Object Detection via Temporal Graph Neural Networks—0
Semi-Supervised 3D Object Detection with Channel Augmentation using Transformation Equivariance—0
Semi-Supervised Stereo-Based 3D Object Detection via Cross-View Consensus—0
Sensor Adversarial Traits: Analyzing Robustness of 3D Object Detection Sensor Fusion Models—0
Sensor Fusion for Joint 3D Object Detection and Semantic Segmentation—0
Shape-Aware Monocular 3D Object Detection—0
Shape Prior Non-Uniform Sampling Guided Real-time Stereo 3D Object Detection—0
Shift R-CNN: Deep Monocular 3D Object Detection with Closed-Form Geometric Constraints—0
siaNMS: Non-Maximum Suppression with Siamese Networks for Multi-Camera 3D Object Detection—0
SimMining-3D: Altitude-Aware 3D Object Detection in Complex Mining Environments: A Novel Dataset and ROS-Based Automatic Annotation Pipeline—0
SimpleBEV: Improved LiDAR-Camera Fusion Architecture for 3D Object Detection—0
Single-Shot 3D Detection of Vehicles from Monocular RGB Images via Geometry Constrained Keypoints in Real-Time—0
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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