atlas

Research map / Detection and segmentation / Weakly supervised detection and segmentation

Instance Localization for Self-Supervised Detection Pretraining

CVPR 2021 · Detection and segmentation › Weakly supervised detection and segmentation · approach: Weakly supervised object localization · 114 citations (OpenAlex)

Check your idea against 108,967 papers

AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.

Measured effects reported in the paper

What was changedWhereMeasuredEffect
pretrain with instance localization using pasted foregrounds and bounding-box region features instead of holistic instance discriminationMoCo-v2, ResNet50-C4 · PASCAL VOC test2007AP: 57.4 -> 58.4Helped
pretrain with instance localization using pasted foregrounds and bounding-box region features instead of holistic instance discriminationMoCo-v2, ResNet50-C4 · COCO val2017, Mask R-CNN 2×APbb: 41.2 -> 41.8Helped
pretrain with instance localization using pasted foregrounds and bounding-box region features instead of holistic instance discriminationMoCo-v2, ResNet50-FPN · COCO val2017, Mask R-CNN 2×APbb: 42.5 -> 43.3Helped
pretrain with instance localizationMoCo-v2, ResNet50-C4 · Mini COCO val2017, 10% trainAPbb: 22.7 -> 26.0Helped
add RoIAlign for architectural alignment (ablation)MoCo-v2, ResNet50-FPN · COCO val2017, 1× ablationAPbb: 39.8 -> 40.2Helped
add copy-paste instance localization and bounding-box representations (ablation)RoIAlign baseline, ResNet50-FPN · COCO val2017, 1× ablationAPbb: 40.2 -> 41.1Helped
add bounding-box augmentation using spatially jittered boxes (ablation)Instance localization, ResNet50-FPN · COCO val2017, 1× ablationAPbb: 41.1 -> 41.4Helped
use instance localization rather than holistic instance discriminationMoCo-v2, ResNet50-C4 · ImageNet linear probeclassification accuracy: 67.7 -> 61.7Hurt
use instance localization rather than holistic instance discriminationMoCo-v2, ResNet50-C4 · Linear localization evaluationlocalization accuracy: 71.9 -> 74.2Helped
increase InsLoc pretraining from 200 to 400 epochsInsLoc, ResNet50-C4 · COCO val2017, Mask R-CNN 2×APbb: 41.4 -> 41.8Helped
increase InsLoc pretraining from 200 to 400 epochsInsLoc, ResNet50-FPN · COCO val2017, Mask R-CNN 2×APbb: 43.2 -> 43.3No clear effect

Closest papers by meaning

Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.

Open scime draft

Get the next scime Dispatch and a monthly field update

Free. We send a confirmation link first; every email has a one-click unsubscribe. Privacy