SOTAVerified

Novel Object Detection

Novel Object Detection is a challenging task introduced by Fomenko et.al. in their paper "Learning to Discover and Detect Objects". The goal in this task is to measure mAP performance on known as well as novel classes, where the known classes correspond to the 80 COCO classes, and the novel classes are the remaining 1123 classes from LVIS dataset. Thus, during training the model can only be trained with annotations from COCO dataset, but during evaluation/inference it is expected to BOTH classify and detect objects belonging to ALL the classes in the LVIS dataset.

Papers

Showing 5153 of 53 papers

TitleStatusHype
Geometry-Based Region Proposals for Real-Time Robot Detection of Tabletop ObjectsCode0
Learning to Detect and Retrieve Objects from Unlabeled VideosCode0
Automatic Signboard Detection and Localization in Densely Populated Developing CitiesCode0
Show:102550
← PrevPage 6 of 6Next →

No leaderboard results yet.