2nd Place Solution for Waymo Open Dataset Challenge -- 2D Object Detection
원문 초록
A practical autonomous driving system urges the need to reliably and accurately detect vehicles and persons. In this report, we introduce a state-of-the-art 2D object detection system for autonomous driving scenarios. Specifically, we integrate both popular two-stage detector and one-stage detector with anchor free fashion to yield a robust detection. Furthermore, we train multiple expert models and design a greedy version of the auto ensemble scheme that automatically merges detections from different models. Notably, our overall detection system achieves 70.28 L2 mAP on the Waymo Open Dataset v1.2, ranking the 2nd place in the 2D detection track of the Waymo Open Dataset Challenges.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Beyond One Shot, Beyond One Perspective: Cross-View and Long-Horizon Distillation for Better LiDAR Representations
Edge-Enabled Collaborative Object Detection for Real-Time Multi-Vehicle Perception
Simulate Any Radar: Attribute-Controllable Radar Simulation via Waveform Parameter Embedding
DuET: Dual Incremental Object Detection via Exemplar-Free Task Arithmetic
Lightweight Multi-Frame Integration for Robust YOLO Object Detection in Videos
A Survey of Multi-sensor Fusion Perception for Embodied AI: Background, Methods, Challenges and Prospects
토론
이 논문과 연결된 포럼 글이 아직 없습니다.