arXiv:2108.04230
공식 코드 · Papers with Code
Workshop on Autonomous Driving at CVPR 2021: Technical Report for Streaming Perception Challenge
원문 초록
In this report, we introduce our real-time 2D object detection system for the realistic autonomous driving scenario. Our detector is built on a newly designed YOLO model, called YOLOX. On the Argoverse-HD dataset, our system achieves 41.0 streaming AP, which surpassed second place by 7.8/6.1 on detection-only track/fully track, respectively. Moreover, equipped with TensorRT, our model achieves the 30FPS inference speed with a high-resolution input size (e.g., 1440-2304). Code and models will be available at https://github.com/Megvii-BaseDetection/YOLOX
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Beyond One Shot, Beyond One Perspective: Cross-View and Long-Horizon Distillation for Better LiDAR Representations
YOLOv13: Real-Time Object Detection with Hypergraph-Enhanced Adaptive Visual Perception
Edge-Enabled Collaborative Object Detection for Real-Time Multi-Vehicle Perception
Simulate Any Radar: Attribute-Controllable Radar Simulation via Waveform Parameter Embedding
Detection of Rail Line Track and Human Beings Near the Track to Avoid Accidents
DuET: Dual Incremental Object Detection via Exemplar-Free Task Arithmetic
토론
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