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 751–800 of 1576 papers

TitleStatusHype
CoBEVFusion: Cooperative Perception with LiDAR-Camera Bird's-Eye View Fusion—0
Cocoon: Robust Multi-Modal Perception with Uncertainty-Aware Sensor Fusion—0
CodeMerge: Codebook-Guided Model Merging for Robust Test-Time Adaptation in Autonomous Driving—0
CoFF: Cooperative Spatial Feature Fusion for 3D Object Detection on Autonomous Vehicles—0
Collaborative 3D Object Detection for Automatic Vehicle Systems via Learnable Communications—0
Collective Perception Datasets for Autonomous Driving: A Comprehensive Review—0
Comparative study of 3D object detection frameworks based on LiDAR data and sensor fusion techniques—0
Complete 3d relationships extraction modality alignment network for 3d dense captioning—0
Complexer-YOLO: Real-Time 3D Object Detection and Tracking on Semantic Point Clouds—0
Confidence Guided Stereo 3D Object Detection with Split Depth Estimation—0
Consistency of Implicit and Explicit Features Matters for Monocular 3D Object Detection—0
Context-Aware Data Augmentation for LIDAR 3D Object Detection—0
ContextualFusion: Context-Based Multi-Sensor Fusion for 3D Object Detection in Adverse Operating Conditions—0
ContrastAlign: Toward Robust BEV Feature Alignment via Contrastive Learning for Multi-Modal 3D Object Detection—0
Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds—0
CornerPoint3D: Look at the Nearest Corner Instead of the Center—0
CorrBEV: Multi-View 3D Object Detection by Correlation Learning with Multi-modal Prototypes—0
Cost-Aware Evaluation and Model Scaling for LiDAR-Based 3D Object Detection—0
CP-VoteNet: Contrastive Prototypical VoteNet for Few-Shot Point Cloud Object Detection—0
CRAFT: Camera-Radar 3D Object Detection with Spatio-Contextual Fusion Transformer—0
CramNet: Camera-Radar Fusion with Ray-Constrained Cross-Attention for Robust 3D Object Detection—0
CRKD: Enhanced Camera-Radar Object Detection with Cross-modality Knowledge Distillation—0
Cross-Cluster Shifting for Efficient and Effective 3D Object Detection in Autonomous Driving—0
Cross-Domain Spatial Matching for Camera and Radar Sensor Data Fusion in Autonomous Vehicle Perception System—0
CrossFusion: Interleaving Cross-modal Complementation for Noise-resistant 3D Object Detection—0
Cross-Modality 3D Object Detection—0
CTS: Sim-to-Real Unsupervised Domain Adaptation on 3D Detection—0
CubifAE-3D: Monocular Camera Space Cubification for Auto-Encoder based 3D Object Detection—0
Curiosity-driven 3D Object Detection Without Labels—0
CVFNet: Real-time 3D Object Detection by Learning Cross View Features—0
Cyber Mobility Mirror: A Deep Learning-based Real-World Object Perception Platform Using Roadside LiDAR—0
Cycle and Semantic Consistent Adversarial Domain Adaptation for Reducing Simulation-to-Real Domain Shift in LiDAR Bird's Eye View—0
Introducing Depth into Transformer-based 3D Object Detection—0
DA-BEV: Unsupervised Domain Adaptation for Bird's Eye View Perception—0
DA-CIL: Towards Domain Adaptive Class-Incremental 3D Object Detection—0
DECADE: Towards Designing Efficient-yet-Accurate Distance Estimation Modules for Collision Avoidance in Mobile Advanced Driver Assistance Systems—0
Decoupled and Interactive Regression Modeling for High-performance One-stage 3D Object Detection—0
Decoupled Pseudo-labeling for Semi-Supervised Monocular 3D Object Detection—0
DeepAccident: A Motion and Accident Prediction Benchmark for V2X Autonomous Driving—0
Deep Camera Pose Regression Using Pseudo-LiDAR—0
Deep Continuous Fusion for Multi-Sensor 3D Object Detection—0
Deep Fitting Degree Scoring Network for Monocular 3D Object Detection—0
DeepFusion: A Robust and Modular 3D Object Detector for Lidars, Cameras and Radars—0
DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection—0
Deep learning for 3D Object Detection and Tracking in Autonomous Driving: A Brief Survey—0
Deep Learning of Local RGB-D Patches for 3D Object Detection and 6D Pose Estimation—0
Deep Learning on Radar Centric 3D Object Detection—0
Deep Optics for Monocular Depth Estimation and 3D Object Detection—0
Deep Reinforcement Learning-Based User Scheduling for Collaborative Perception—0
Deep SCNN-based Real-time Object Detection for Self-driving Vehicles Using LiDAR Temporal Data—0
Show:102550
← PrevPage 16 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