Methods › Computer Vision › One-Stage Object Detection Models › CornerNet-Saccade

CornerNet-Saccade

1 paper tagged archive 2025-07-28

Introduced by Hei Law et al. in CornerNet-Lite: Efficient Keypoint Based Object Detection

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

CornerNet-Saccade is an extension of CornerNet with an attention mechanism similar to saccades in human vision. It starts with a downsized full image and generates an attention map, which is then zoomed in on and processed further by the model. This differs from the original CornerNet in that it is applied fully convolutionally across multiple scales.

PaperSourceSee Code · princeton-vl/CornerNet-Lite

Papers archive 2025-07-28

1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

4 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Object1
Object Detection1
Real-Time Object Detection1
object-detection1

Usage over time archive 2025-07-28

Papers per year tagged with CornerNet-Saccade: 2019 to 2019, peak 1 1 0 2019: 1 paper 2019
Papers per year the archive tags with this method, by the paper's archive date (1 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

One-Stage Object Detection ModelsObject Detection Models

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