Continuous-time Intensity Estimation Using Event Cameras
November 01, 2018 ยท Declared Dead ยท ๐ Asian Conference on Computer Vision
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Cedric Scheerlinck, Nick Barnes, Robert Mahony
arXiv ID
1811.00386
Category
cs.CV: Computer Vision
Citations
228
Venue
Asian Conference on Computer Vision
Last Checked
2 months ago
Abstract
Event cameras provide asynchronous, data-driven measurements of local temporal contrast over a large dynamic range with extremely high temporal resolution. Conventional cameras capture low-frequency reference intensity information. These two sensor modalities provide complementary information. We propose a computationally efficient, asynchronous filter that continuously fuses image frames and events into a single high-temporal-resolution, high-dynamic-range image state. In absence of conventional image frames, the filter can be run on events only. We present experimental results on high-speed, high-dynamic-range sequences, as well as on new ground truth datasets we generate to demonstrate the proposed algorithm outperforms existing state-of-the-art methods.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Computer Vision
๐
๐
Old Age
๐
๐
Old Age
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
R.I.P.
๐ป
Ghosted
You Only Look Once: Unified, Real-Time Object Detection
๐
๐
Old Age
SSD: Single Shot MultiBox Detector
๐
๐
Old Age
Squeeze-and-Excitation Networks
R.I.P.
๐ป
Ghosted
Rethinking the Inception Architecture for Computer Vision
Died the same way โ ๐ป Ghosted
R.I.P.
๐ป
Ghosted
Language Models are Few-Shot Learners
R.I.P.
๐ป
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
๐ป
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
๐ป
Ghosted