atlas

Research map / Detection and segmentation / Open-set and few-shot detection

Exemplar-FreeSOLO: Enhancing Unsupervised Instance Segmentation With Exemplars

CVPR 2023 · Detection and segmentation › Open-set and few-shot detection · approach: Amodal and open-world instance segmentation · 8 citations (OpenAlex)

Read the paperCheck 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
add exemplar knowledge abstraction and exemplar embedding contrastive guidanceFreeSOLO · MS COCO val2017 instance segmentationAP: 4.0 -> 8.4Helped
add exemplar knowledge abstraction and exemplar embedding contrastive guidanceFreeSOLO object detection · MS COCO val2017AP: 5.5 -> 12.6Helped
add exemplar knowledge abstraction and exemplar embedding contrastive guidanceFreeSOLO · UVO val instance segmentationAP: 4.8 -> 9.2Helped
add exemplar knowledge abstraction and exemplar embedding contrastive guidanceFreeSOLO · PASCAL VOC trainval07 multi-object discoveryAP: 10.2 -> 12.6Helped
replace the unsupervised exemplar mechanism with box ground-truth foreground supervision (ablation)Exemplar-FreeSOLO · MS COCO val2017 instance segmentationAP: 8.4 -> 5.8Hurt
replace the unsupervised exemplar mechanism with mask ground-truth foreground supervision (ablation)Exemplar-FreeSOLO · MS COCO val2017 instance segmentationAP: 8.4 -> 6.2Hurt
replace the unsupervised exemplar mechanism with box ground-truth foreground supervision (ablation)Exemplar-FreeSOLO object detection · MS COCO val2017AP: 12.6 -> 7.1Hurt
replace the unsupervised exemplar mechanism with mask ground-truth foreground supervision (ablation)Exemplar-FreeSOLO object detection · MS COCO val2017AP: 12.6 -> 8.2Hurt
increase the number of exemplar objects per category from 1 to 9 (ablation)Exemplar-FreeSOLO · MS COCO val2017 instance segmentationAP: 8.4 -> 8.9Helped
increase the number of exemplar objects per category from 1 to 9 (ablation)Exemplar-FreeSOLO object detection · MS COCO val2017AP: 12.6 -> 13.0Helped
vary the exemplar embedding contrastive loss weight (ablation)Exemplar-FreeSOLO · MS COCO val2017 instance segmentationAP: 7.6, 7.6, 8.8, 8.8, 8.2, 8.2, 8.4, 8.1Mixed
vary the exemplar embedding contrastive loss weight (ablation)Exemplar-FreeSOLO object detection · MS COCO val2017AP: 10.8, 10.7, 11.1, 11.9, 12.0, 12.2, 12.6, 11.8Mixed

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