mlsanityData to 7 Oct 2026

Open World Object Detection: A Survey

arXiv 2410.11301 ↗First posted 15 Oct 2024cs.CVcited by 13

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Abstract (arXiv)

Exploring new knowledge is a fundamental human ability that can be mirrored in the development of deep neural networks, especially in the field of object detection. Open world object detection (OWOD) is an emerging area of research that adapts this principle to explore new knowledge. It focuses on recognizing and learning from objects absent from initial training sets, thereby incrementally expanding its knowledge base when new class labels are introduced. This survey paper offers a thorough review of the OWOD domain, covering essential aspects, including problem definitions, benchmark datasets, source codes, evaluation metrics, and a comparative study of existing methods. Additionally, we investigate related areas like open set recognition (OSR) and incremental learning (IL), underlining their relevance to OWOD. Finally, the paper concludes by addressing the limitations and challenges faced by current OWOD algorithms and proposes directions for future research. To our knowledge, this is the first comprehensive survey of the emerging OWOD field with over one hundred references, marking a significant step forward for object detection technology. A comprehensive source code and benchmarks are archived and concluded at https://github.com/ArminLee/OWOD Review.

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). Builds on 96 of its 125 references that are in the map. First posted on arXiv 15 Oct 2024.

Builds on

96 of 125 references.

References · 96

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38 more
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50 most cited of 96 All 96 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 7; 2026: 6.

13 papers.

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  1. 2025Consistent Supervised-Unsupervised Alignment for Generalized Category Discoverycited by 5
  2. 20253DGeoDet: General-purpose Geometry-aware Image-based 3D Object Detectioncited by 3
  3. 2025EDVD-LLaMA: Explainable Deepfake Video Detection via Multimodal Large Language Model Reasoningcited by 2
  4. 2026TSBOW -- Traffic Surveillance Benchmark for Occluded Vehicles Under Various Weather Conditionscited by 2
  5. 2026DAOS: A Multimodal In-cabin Behavior Monitoring with Driver Action-Object Synergy Datasetcited by 1
  6. 2026REAL-OW: Rehearsal-free Open World Object Detection with Low-Rank Adaptation and Dual-Stage Objectness Modelingcited by 1
  7. 2026Continual Test-Time Adaptation in Computer Vision: Methods, Benchmarks, and Future Directionscited by 1
  8. 2025MVT: Mask-Grounded Vision-Language Models for Taxonomy-Aligned Land-Cover Taggingcited by 0
  9. 2025HSNet: Heterogeneous Subgraph Network for Single Image Super-resolutioncited by 0
  10. 2025Operon: Incremental Construction of Ragged Data via Named Dimensionscited by 0
  11. 2025GVSynergy-Det: Synergistic Gaussian-Voxel Representations for Multi-View 3D Object Detectioncited by 0
  12. 2026CODE: Cross-Modal Calibration and Dynamic Suppression for Open World Object Detectioncited by 0
1 more
  1. 2026Hyperbolic Geometry for Open-World Object Detection in Remote Sensing Imagerycited by 0