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 14611470 of 1576 papers

TitleStatusHype
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
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1EA-LSSNDS0.78Unverified
2MMFusion-eNDS0.77Unverified
3MegFusionNDS0.77Unverified
4RacoonPowerNDS0.76Unverified
5BEVFusion-eNDS0.76Unverified
6DeepInteraction-largeNDS0.76Unverified
7DeepInteraction-eNDS0.76Unverified
8DAANDS0.75Unverified
9FusionVPENDS0.75Unverified
10CenterPoint-FusionNDS0.75Unverified