TADP: Task-Aware Deformable Prediction for Single-Stage 3D Object Detection

arXiv:2608.27282 · cs.CV, cs.AI, cs.RO, cs.SY, eess.SY · Submitted 2026-08-27 · Read on arXiv

cs.CV, cs.AI, cs.RO, cs.SY, eess.SY

Submitted: 2026-08-27

Updated: 2026-08-27

Comments: Accepted to the 2023 IEEE Intelligent Vehicles Symposium (IV 2023)

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Accuracy — 18× in this paper · explained in 1 episode
• Aggregation — 14× in this paper · explained in 1 episode
• Point Clouds — 10× in this paper · explained in 2 episodes
• Benchmark — 6× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 5× in this paper
• Transformer — 5× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Feature Extraction — 2× in this paper · explained in 2 episodes
• Loss Function — 2× in this paper · explained in 2 episodes
• Activation Function — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Guided attention — 1× in this paper · explained in 2 episodes
• Muti-Scale Feature Aggregation — 1× in this paper
• Sparsity — 1× in this paper · explained in 4 episodes
• Task-Aware Deformable Detection Head — 1× in this paper

Sources

• Voxel R-CNN: Towards High Performance Voxel-based 3D Object Detection
• Embracing Single Stride 3D Object Detector with Sparse Transformer
• Not All Points Are Equal: Learning Highly Efficient Point-based Detectors for 3D LiDAR Point Clouds
• From Points to Parts: 3D Object Detection from Point Cloud with Part-aware and Part-aggregation Network

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