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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 711–720 of 1576 papers

TitleStatusHype
DOPS: Learning to Detect 3D Objects and Predict their 3D Shapes—0
LXLv2: Enhanced LiDAR Excluded Lean 3D Object Detection with Fusion of 4D Radar and Camera—0
Domain Adaptation in 3D Object Detection with Gradual Batch Alternation Training—0
Divide and Conquer: Improving Multi-Camera 3D Perception with 2D Semantic-Depth Priors and Input-Dependent Queries—0
DM3D: Distortion-Minimized Weight Pruning for Lossless 3D Object Detection—0
Boosting Single-Frame 3D Object Detection by Simulating Multi-Frame Point Clouds—0
M^2BEV: Multi-Camera Joint 3D Detection and Segmentation with Unified Birds-Eye View Representation—0
Diversity Matters: Fully Exploiting Depth Clues for Reliable Monocular 3D Object Detection—0
Boosting Monocular 3D Object Detection with Object-Centric Auxiliary Depth Supervision—0
Boosting 3D Object Detection with Semantic-Aware Multi-Branch Framework—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
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