Papers › Reducing the Sim-to-Real Gap for Event Cameras
Reducing the Sim-to-Real Gap for Event Cameras
Timo Stoffregen, Cedric Scheerlinck, Davide Scaramuzza, Tom Drummond, Nick Barnes, Lindsay Kleeman, Robert Mahony
Event cameras are paradigm-shifting novel sensors that report asynchronous, per-pixel brightness changes called 'events' with unparalleled low latency. This makes them ideal for high speed, high dynamic range scenes where conventional cameras would fail. Recent work has demonstrated impressive results using Convolutional Neural Networks (CNNs) for video reconstruction and optic flow with events. We present strategies for improving training data for event based CNNs that result in 20-40% boost in performance of existing state-of-the-art (SOTA) video reconstruction networks retrained with our method, and up to 15% for optic flow networks. A challenge in evaluating event based video reconstruction is lack of quality ground truth images in existing datasets. To address this, we present a new High Quality Frames (HQF) dataset, containing events and ground truth frames from a DAVIS240C that are well-exposed and minimally motion-blurred. We evaluate our method on HQF + several existing major event camera datasets.
Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Video Reconstruction | Event-Camera Dataset | E2VID+ | LPIPS | 0.236 | #3 of 4 | Archive leaderboard | report |
| Video Reconstruction | Event-Camera Dataset | E2VID+ | Mean Squared Error | 0.070 | #3 of 4 | Archive leaderboard | report |
| Video Reconstruction | MVSEC | E2VID+ | LPIPS | 0.514 | #3 of 4 | Archive leaderboard | report |
| Video Reconstruction | MVSEC | E2VID+ | Mean Squared Error | 0.132 | #3 of 4 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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