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 1451–1475 of 1576 papers

TitleStatusHype
3D Object Detection from Point Cloud via Voting Step DiffusionCode0
Focal Loss in 3D Object DetectionCode0
PSA-SSL: Pose and Size-aware Self-Supervised Learning on LiDAR Point CloudsCode0
Prompt3D: Random Prompt Assisted Weakly-Supervised 3D Object DetectionCode0
Pre-Training LiDAR-Based 3D Object Detectors Through ColorizationCode0
VCVW-3D: A Virtual Construction Vehicles and Workers Dataset with 3D AnnotationsCode0
Pragmatic Communication in Multi-Agent Collaborative PerceptionCode0
FM-OV3D: Foundation Model-based Cross-modal Knowledge Blending for Open-Vocabulary 3D DetectionCode0
Point-Voxel CNN for Efficient 3D Deep LearningCode0
Simulation-Based Performance Evaluation of 3D Object Detection Methods with Deep Learning for a LiDAR Point Cloud Dataset in a SOTIF-related Use CaseCode0
FFAM: Feature Factorization Activation Map for Explanation of 3D DetectorsCode0
CT3D++: Improving 3D Object Detection with Keypoint-induced Channel-wise TransformerCode0
Exploring Diversity-based Active Learning for 3D Object Detection in Autonomous DrivingCode0
PointSeg: Real-Time Semantic Segmentation Based on 3D LiDAR Point CloudCode0
Cross-Modal Self-Supervised Learning with Effective Contrastive Units for LiDAR Point CloudsCode0
Snow Removal for LiDAR Point Clouds with Spatio-temporal Conditional Random FieldsCode0
Explore the LiDAR-Camera Dynamic Adjustment Fusion for 3D Object DetectionCode0
Point-LGMask: Local and Global Contexts Embedding for Point Cloud Pre-training with Multi-Ratio MaskingCode0
PointFusion: Deep Sensor Fusion for 3D Bounding Box EstimationCode0
Context-Aware Dynamic Feature Extraction for 3D Object Detection in Point CloudsCode0
Perspective-aware Convolution for Monocular 3D Object DetectionCode0
SpaRC: Sparse Radar-Camera Fusion for 3D Object DetectionCode0
Paint and Distill: Boosting 3D Object Detection with Semantic Passing NetworkCode0
Orthographic Feature Transform for Monocular 3D Object DetectionCode0
3D Object Detection From LiDAR Data Using Distance Dependent Feature ExtractionCode0
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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