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 951–1000 of 1576 papers

TitleStatusHype
Multimodal Object Query Initialization for 3D Object Detection—0
GraphAlign: Enhancing Accurate Feature Alignment by Graph matching for Multi-Modal 3D Object Detection—0
3DS-SLAM: A 3D Object Detection based Semantic SLAM towards Dynamic Indoor Environments—0
V2X-AHD:Vehicle-to-Everything Cooperation Perception via Asymmetric Heterogenous Distillation NetworkCode0
Care3D: An Active 3D Object Detection Dataset of Real Robotic-Care EnvironmentsCode0
Rotation Matters: Generalized Monocular 3D Object Detection for Various Camera Systems—0
Joint object detection and re-identification for 3D obstacle multi-camera systems—0
CoBEVFusion: Cooperative Perception with LiDAR-Camera Bird's-Eye View Fusion—0
Anyview: Generalizable Indoor 3D Object Detection with Variable Frames—0
Towards Fair and Comprehensive Comparisons for Image-Based 3D Object DetectionCode0
QE-BEV: Query Evolution for Bird's Eye View Object Detection in Varied ContextsCode0
Towards Long-Range 3D Object Detection for Autonomous Vehicles—0
LS-VOS: Identifying Outliers in 3D Object Detections Using Latent Space Virtual Outlier Synthesis—0
Every Dataset Counts: Scaling up Monocular 3D Object Detection with Joint Datasets Training—0
Towards Robust 3D Object Detection In Rainy Conditions—0
Pixel-Aligned Recurrent Queries for Multi-View 3D Object Detection—0
MonoGAE: Roadside Monocular 3D Object Detection with Ground-Aware Embeddings—0
BEVHeight++: Toward Robust Visual Centric 3D Object Detection—0
LEF: Late-to-Early Temporal Fusion for LiDAR 3D Object Detection—0
M^2SODAI: Multi-Modal Maritime Object Detection Dataset With RGB and Hyperspectral Image Sensors—0
Unsupervised Domain Adaptation for Self-Driving from Past Traversal FeaturesCode0
Shape Anchor Guided Holistic Indoor Scene UnderstandingCode0
SPOT: Scalable 3D Pre-training via Occupancy Prediction for Learning Transferable 3D Representations—0
Object2Scene: Putting Objects in Context for Open-Vocabulary 3D Detection—0
MEDL-U: Uncertainty-aware 3D Automatic Annotation based on Evidential Deep LearningCode0
Mutual Information-calibrated Conformal Feature Fusion for Uncertainty-Aware Multimodal 3D Object Detection at the Edge—0
Semantics-aware LiDAR-Only Pseudo Point Cloud Generation for 3D Object Detection—0
Polygon Intersection-over-Union Loss for Viewpoint-Agnostic Monocular 3D Vehicle Detection—0
SCP: Scene Completion Pre-training for 3D Object Detection—0
FusionFormer: A Multi-sensory Fusion in Bird's-Eye-View and Temporal Consistent Transformer for 3D Object Detection—0
Weakly Supervised Point Clouds Transformer for 3D Object Detection—0
Poster: Making Edge-assisted LiDAR Perceptions Robust to Lossy Point Cloud Compression—0
ClusterFusion: Leveraging Radar Spatial Features for Radar-Camera 3D Object Detection in Autonomous Vehicles—0
Diffusion-based 3D Object Detection with Random Boxes—0
Snow Removal for LiDAR Point Clouds with Spatio-temporal Conditional Random FieldsCode0
Adv3D: Generating 3D Adversarial Examples for 3D Object Detection in Driving Scenarios with NeRF—0
S^3-MonoDETR: Supervised Shape&Scale-perceptive Deformable Transformer for Monocular 3D Object DetectionCode0
MS23D: A 3D Object Detection Method Using Multi-Scale Semantic Feature Points to Construct 3D Feature Layer—0
3D Adversarial Augmentations for Robust Out-of-Domain Predictions—0
Ego-Motion Estimation and Dynamic Motion Separation from 3D Point Clouds for Accumulating Data and Improving 3D Object Detection—0
Group Regression for Query Based Object Detection and Tracking—0
I3DOD: Towards Incremental 3D Object Detection via Prompting—0
On Offline Evaluation of 3D Object Detection for Autonomous Driving—0
Perspective-aware Convolution for Monocular 3D Object DetectionCode0
Advancements in Point Cloud Data Augmentation for Deep Learning: A Survey—0
QD-BEV : Quantization-aware View-guided Distillation for Multi-view 3D Object Detection—0
ThermRad: A Multi-modal Dataset for Robust 3D Object Detection under Challenging Conditions—0
Representation Disparity-aware Distillation for 3D Object Detection—0
PatchContrast: Self-Supervised Pre-training for 3D Object Detection—0
UniWorld: Autonomous Driving Pre-training via World ModelsCode0
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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