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 26–50 of 1576 papers

TitleStatusHype
Floating Car Observers in Intelligent Transportation Systems: Detection Modeling and Temporal Insights—0
A Review of 3D Object Detection with Vision-Language Models—0
A Multimodal Hybrid Late-Cascade Fusion Network for Enhanced 3D Object DetectionCode1
Lightweight LiDAR-Camera 3D Dynamic Object Detection and Multi-Class Trajectory PredictionCode1
Weak Cube R-CNN: Weakly Supervised 3D Detection using only 2D Bounding Boxes—0
RoPETR: Improving Temporal Camera-Only 3D Detection by Integrating Enhanced Rotary Position Embedding—0
Self-Supervised Pre-training with Combined Datasets for 3D Perception in Autonomous Driving—0
GATE3D: Generalized Attention-based Task-synergized Estimation in 3D*—0
RICCARDO: Radar Hit Prediction and Convolution for Camera-Radar 3D Object DetectionCode0
Detect Anything 3D in the WildCode3
PRIMEDrive-CoT: A Precognitive Chain-of-Thought Framework for Uncertainty-Aware Object Interaction in Driving Scene Scenario—0
Inverse++: Vision-Centric 3D Semantic Occupancy Prediction Assisted with 3D Object DetectionCode0
PF3Det: A Prompted Foundation Feature Assisted Visual LiDAR 3D Detector—0
ZFusion: An Effective Fuser of Camera and 4D Radar for 3D Object Perception in Autonomous Driving—0
CornerPoint3D: Look at the Nearest Corner Instead of the Center—0
Multimodal Fusion and Vision-Language Models: A Survey for Robot VisionCode1
Learning Class Prototypes for Unified Sparse Supervised 3D Object DetectionCode1
SaViD: Spectravista Aesthetic Vision Integration for Robust and Discerning 3D Object Detection in Challenging EnvironmentsCode0
DynOPETs: A Versatile Benchmark for Dynamic Object Pose Estimation and Tracking in Moving Camera ScenariosCode1
Hyperdimensional Uncertainty Quantification for Multimodal Uncertainty Fusion in Autonomous Vehicles Perception—0
Hi-ALPS -- An Experimental Robustness Quantification of Six LiDAR-based Object Detection Systems for Autonomous Driving—0
Which2comm: An Efficient Collaborative Perception Framework for 3D Object Detection—0
Uncertainty Meets Diversity: A Comprehensive Active Learning Framework for Indoor 3D Object Detection—0
PSA-SSL: Pose and Size-aware Self-Supervised Learning on LiDAR Point CloudsCode0
State Space Model Meets Transformer: A New Paradigm for 3D Object DetectionCode1
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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
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