Open World Object Detection

22 papers with code • 7 benchmarks • 5 datasets

Open World Object Detection is a computer vision problem where a model is tasked to: 1) identify objects that have not been introduced to it as `unknown', without explicit supervision to do so, and 2) incrementally learn these identified unknown categories without forgetting previously learned classes, when the corresponding labels are progressively received.

Most implemented papers

Learning Open-World Object Proposals without Learning to Classify

mcahny/object_localization_network 15 Aug 2021

In this paper, we identify that the problem is that the binary classifiers in existing proposal methods tend to overfit to the training categories.

Towards Open World Object Detection

JosephKJ/OWOD CVPR 2021

Humans have a natural instinct to identify unknown object instances in their environments.

OW-DETR: Open-world Detection Transformer

akshitac8/ow-detr CVPR 2022

In the case of incremental object detection, OW-DETR outperforms the state-of-the-art for all settings on PASCAL VOC.

Hyp-OW: Exploiting Hierarchical Structure Learning with Hyperbolic Distance Enhances Open World Object Detection

boschresearch/hyp-ow 25 Jun 2023

We argue that this contextual information should already be embedded within the known classes.

Class-agnostic Object Detection with Multi-modal Transformer

mmaaz60/mvits_for_class_agnostic_od 22 Nov 2021

This has been a long-standing question in computer vision.

Revisiting Open World Object Detection

re-owod/re-owod 3 Jan 2022

Open World Object Detection (OWOD), simulating the real dynamic world where knowledge grows continuously, attempts to detect both known and unknown classes and incrementally learn the identified unknown ones.

Localized Vision-Language Matching for Open-vocabulary Object Detection

lmb-freiburg/locov 12 May 2022

In this work, we propose an open-vocabulary object detection method that, based on image-caption pairs, learns to detect novel object classes along with a given set of known classes.

UC-OWOD: Unknown-Classified Open World Object Detection

johnwuzh/uc-owod 23 Jul 2022

In this work, we propose a novel OWOD problem called Unknown-Classified Open World Object Detection (UC-OWOD).

PROB: Probabilistic Objectness for Open World Object Detection

orrzohar/prob CVPR 2023

The resulting Probabilistic Objectness transformer-based open-world detector, PROB, integrates our framework into traditional object detection models, adapting them for the open-world setting.

GOOD: Exploring Geometric Cues for Detecting Objects in an Open World

autonomousvision/good 22 Dec 2022

We address the task of open-world class-agnostic object detection, i. e., detecting every object in an image by learning from a limited number of base object classes.