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 301–325 of 1576 papers

TitleStatusHype
LSSInst: Improving Geometric Modeling in LSS-Based BEV Perception with Instance RepresentationCode1
Learning Occupancy for Monocular 3D Object DetectionCode1
Efficient Feature Aggregation and Scale-Aware Regression for Monocular 3D Object DetectionCode1
Learning to Detect Objects from Multi-Agent LiDAR Scans without Manual LabelsCode1
DynOPETs: A Versatile Benchmark for Dynamic Object Pose Estimation and Tracking in Moving Camera ScenariosCode1
Learning Object-level Point Augmentor for Semi-supervised 3D Object DetectionCode1
LEROjD: Lidar Extended Radar-Only Object DetectionCode1
CRT-Fusion: Camera, Radar, Temporal Fusion Using Motion Information for 3D Object DetectionCode1
Dual Radar: A Multi-modal Dataset with Dual 4D Radar for Autonomous DrivingCode1
3D Object Detection from Images for Autonomous Driving: A SurveyCode1
Cross-Modality Knowledge Distillation Network for Monocular 3D Object DetectionCode1
Learning from Noisy Data for Semi-Supervised 3D Object DetectionCode1
CubeSLAM: Monocular 3D Object SLAMCode1
AYDIV: Adaptable Yielding 3D Object Detection via Integrated Contextual Vision TransformerCode1
Learning Geometry-Guided Depth via Projective Modeling for Monocular 3D Object DetectionCode1
EarlyBird: Early-Fusion for Multi-View Tracking in the Bird's Eye ViewCode1
Curricular Object Manipulation in LiDAR-based Object DetectionCode1
Back to Reality: Weakly-supervised 3D Object Detection with Shape-guided Label EnhancementCode1
DualDiff+: Dual-Branch Diffusion for High-Fidelity Video Generation with Reward GuidanceCode1
A Comprehensive Study of the Robustness for LiDAR-based 3D Object Detectors against Adversarial AttacksCode1
DualDiff: Dual-branch Diffusion Model for Autonomous Driving with Semantic FusionCode1
CrossDTR: Cross-view and Depth-guided Transformers for 3D Object DetectionCode1
Enhancing 3D Object Detection with 2D Detection-Guided Query AnchorsCode1
AutoShape: Real-Time Shape-Aware Monocular 3D Object DetectionCode1
Learning High-resolution Vector Representation from Multi-Camera Images 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
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