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

Showing 151160 of 1576 papers

TitleStatusHype
Objects as PointsCode2
nuScenes: A multimodal dataset for autonomous drivingCode2
PointPillars: Fast Encoders for Object Detection from Point CloudsCode2
SECOND: Sparsely Embedded Convolutional DetectionCode2
Complex-YOLO: Real-time 3D Object Detection on Point CloudsCode2
Beyond One Shot, Beyond One Perspective: Cross-View and Long-Horizon Distillation for Better LiDAR RepresentationsCode1
DualDiff: Dual-branch Diffusion Model for Autonomous Driving with Semantic FusionCode1
A Multimodal Hybrid Late-Cascade Fusion Network for Enhanced 3D Object DetectionCode1
Lightweight LiDAR-Camera 3D Dynamic Object Detection and Multi-Class Trajectory PredictionCode1
Multimodal Fusion and Vision-Language Models: A Survey for Robot VisionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1EA-LSSNDS0.78Unverified
2MegFusionNDS0.77Unverified
3MMFusion-eNDS0.77Unverified
4BEVFusion-eNDS0.76Unverified
5RacoonPowerNDS0.76Unverified
6DeepInteraction-largeNDS0.76Unverified
7DeepInteraction-eNDS0.76Unverified
8FusionVPENDS0.75Unverified
9FocalFormer3D-FNDS0.75Unverified
10CenterPoint-FusionNDS0.75Unverified