demo · HACKER NEWS RECOMMENDATION
CVPR 2018: Learning to See in the Dark
Chen Chen · 1 HN recommenders · 1 recommendation months
Recommended by 1 Hacker News commenters across 1 months (2018–2020).
SignalTube analysis
Among 35 other demo videos tagged Computer vision, speech & NLP, the mean is 1.0 distinct HN recommenders. This video has 1 distinct HN recommenders, close to that mean. Recommendations span 1 distinct month; the peer average is 1.0 months. This is a data-derived comparison, not a human review or quality rating.
33% of its 3 labeled comments are marked as recommendations or strong recommendations. HN mention years are 2018–2020; those years describe discussion history, not upload date. Its verified runtime is 3 minutes 31 seconds. YouTube lists its publication date as 2018-04-24.
- Channel / speaker
- Chen Chen
- Verified runtime
- 3m 31s
- YouTube upload date
- 2018-04-24
- Hacker News mention years
- 2018–2020
SAME TOPIC AND FORMAT
Compare with related videos
The comparison cohort uses other demo videos in Computer vision, speech & NLP. “Shared recommenders” counts HN users who recommended both videos in the source graph.
| Video | HN recommenders | Recommendation months | Positive label share | Shared recommenders | Runtime | Upload date |
|---|---|---|---|---|---|---|
| CVPR 2018: Learning to See in the DarkCurrent video | 1 | 1 | 33% | — | 3m 31s | 2018-04-24 |
| Dual Photographydemo · mm648230 | 4 | 4 | 40% | No recorded overlap | 5m 10s | 2009-03-28 |
| Stealing Baseball Signs with a Phone (Machine Learning)demo · Mark Rober | 3 | 3 | 60% | No recorded overlap | 13m 30s | 2019-06-30 |
| Speaking Piano - Now with (somewhat decent) captions!demo · TheMcphearson | 3 | 3 | 60% | No recorded overlap | 2m 41s | 2009-10-05 |
THREE SOURCE-BASED CONTEXT POINTS
Why Hacker News recommends it
Each note combines the dataset’s stance label and short rationale; comment bodies are not reproduced. Open the HN source for the original discussion.
The archive classifies this as a contextual reference in “Learning to See in the Dark (2018)”. Its short rationale: Video shows comparison against denoising approaches.
The archive classifies this as a contextual reference in “Why OpenCV uses BGR color space (2015)”. Its short rationale: Cited as example of training on raw images improving enhancement.
The archive classifies this as a recommendation in “Learning to See in the Dark”. Its short rationale: Remarkable low-light image enhancement result.