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 481490 of 1576 papers

TitleStatusHype
Diffusion-SS3D: Diffusion Model for Semi-supervised 3D Object DetectionCode1
BEVNeXt: Reviving Dense BEV Frameworks for 3D Object DetectionCode1
Exploring Adversarial Robustness of LiDAR-Camera Fusion Model in Autonomous Driving0
Towards Efficient 3D Object Detection in Bird's-Eye-View Space for Autonomous Driving: A Convolutional-Only Approach0
PillarNeSt: Embracing Backbone Scaling and Pretraining for Pillar-based 3D Object Detection0
OneFormer3D: One Transformer for Unified Point Cloud SegmentationCode2
Towards Transferable Multi-modal Perception Representation Learning for Autonomy: NeRF-Supervised Masked AutoEncoder0
FlashOcc: Fast and Memory-Efficient Occupancy Prediction via Channel-to-Height PluginCode2
Point Cloud Self-supervised Learning via 3D to Multi-view Masked AutoencoderCode1
Domain Generalization of 3D Object Detection by Density-ResamplingCode0
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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