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Open World Object Detection

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.

Papers

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Showing 26–50 of 50 papers

TitleStatusHype
Revisiting Open World Object DetectionCode1
OW-DETR: Open-world Detection TransformerCode1
Class-agnostic Object Detection with Multi-modal TransformerCode1
Learning Open-World Object Proposals without Learning to ClassifyCode1
Towards Open World Object DetectionCode1
Decoupled PROB: Decoupled Query Initialization Tasks and Objectness-Class Learning for Open World Object Detection—0
SAM2Auto: Auto Annotation Using FLASH—0
VL-SAM-V2: Open-World Object Detection with General and Specific Query Fusion—0
Open-World Objectness Modeling Unifies Novel Object Detection—0
Detecting Open World Objects via Partial Attribute Assignment—0
UADet: A Remarkably Simple Yet Effective Uncertainty-Aware Open-Set Object Detection Framework—0
OW-Rep: Open World Object Detection with Instance Representation Learning—0
Finding Dino: A plug-and-play framework for unsupervised detection of out-of-distribution objects using prototypes—0
YOLOOC: YOLO-based Open-Class Incremental Object Detection with Novel Class Discovery—0
BSDP: Brain-inspired Streaming Dual-level Perturbations for Online Open World Object Detection—0
Open World Object Detection in the Era of Foundation Models—0
USD: Unknown Sensitive Detector Empowered by Decoupled Objectness and Segment Anything Model—0
Addressing the Challenges of Open-World Object Detection—0
Open-World Object Detection via Discriminative Class Prototype Learning—0
CAT: LoCalization and IdentificAtion Cascade Detection Transformer for Open-World Object Detection—0
Open World DETR: Transformer based Open World Object Detection—0
DetCLIP: Dictionary-Enriched Visual-Concept Paralleled Pre-training for Open-world Detection—0
Rectifying Open-set Object Detection: A Taxonomy, Practical Applications, and Proper Evaluation—0
Contrastive Object Detection Using Knowledge Graph Embeddings—0
Objects in Semantic Topology—0
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