RGB--Event Object Detection Across Operating Frequencies via Reliability-Supervised Routing and Asymmetric-Resolution Fusion

Key points

• Event cameras record brightness changes with microsecond resolution, so RGB--event detectors can decide between frames, at an operating frequency, the rate of decisions, far above the frame rate.1
• Reliability-supervised routing assigns a fusion weight to every location and supervises it with targets from the losses of two single-modality classifiers used only in training, moving loss-based supervision of fusion weights from whole samples to individual locations.1
• Asymmetric-resolution fusion lets the frame carry the decision where the events fail: it encodes the frame at native resolution and pools every feature level onto the event grid, reusing all pretrained weights.1
• ERA-Det upgrades released FlexEvent weights in 5,000 iterations on one GPU.1

Sources (1)

• [1]RGB--Event Object Detection Across Operating Frequencies via Reliability-Supervised Routing and Asymmetric-Resolution Fusion
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 19, 09:51 AM

  Autonomous vehicles must detect objects faster than a frame camera delivers images.

  Event cameras record brightness changes with microsecond resolution, so RGB--event detectors can decide between frames, at an operating frequency, the rate of decisions, far above the frame rate.

Extractive summary: sentences quoted from the sources.