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 1431–1440 of 1576 papers

TitleStatusHype
Self-Supervised 3D Monocular Object Detection by Recycling Bounding Boxes—0
Self-supervised 3D Object Detection from Monocular Pseudo-LiDAR—0
Self-supervised cross-modality learning for uncertainty-aware object detection and recognition in applications which lack pre-labelled training data—0
Self-Supervised Pre-training with Combined Datasets for 3D Perception in Autonomous Driving—0
SemanticBEVFusion: Rethink LiDAR-Camera Fusion in Unified Bird's-Eye View Representation for 3D Object Detection—0
Semantics-aware LiDAR-Only Pseudo Point Cloud Generation for 3D Object Detection—0
Semantic-Supervised Spatial-Temporal Fusion for LiDAR-based 3D Object Detection—0
Semi-supervised 3D Object Detection via Adaptive Pseudo-Labeling—0
Semi-supervised 3D Object Detection via Temporal Graph Neural Networks—0
Semi-Supervised 3D Object Detection with Channel Augmentation using Transformation Equivariance—0
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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