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Found 6 papers, 6 papers with code
Class-balanced Grouping and Sampling for Point Cloud 3D Object Detection
This report presents our method which wins the nuScenes3D Detection Challenge [17] held in Workshop on Autonomous Driving(WAD, CVPR 2019).
Ranked #5 on
3D Object Detection
on nuScenes LiDAR only
AutoAssign: Differentiable Label Assignment for Dense Object Detection
During training, to both satisfy the prior distribution of data and adapt to category characteristics, we present Center Weighting to adjust the category-specific prior distributions.
EqCo: Equivalent Rules for Self-supervised Contrastive Learning
In this paper, we propose EqCo (Equivalent Rules for Contrastive Learning) to make self-supervised learning irrelevant to the number of negative samples in the contrastive learning framework.
MPPNet: Multi-Frame Feature Intertwining with Proxy Points for 3D Temporal Object Detection
Accurate and reliable 3D detection is vital for many applications including autonomous driving vehicles and service robots.
ConQueR: Query Contrast Voxel-DETR for 3D Object Detection
We thus propose a Query Contrast mechanism to explicitly enhance queries towards their best-matched GTs over all unmatched query predictions.
TrajectoryFormer: 3D Object Tracking Transformer with Predictive Trajectory Hypotheses
3D multi-object tracking (MOT) is vital for many applications including autonomous driving vehicles and service robots.
