mlsanityData to 7 Oct 2026

Wanderlust: Online Continual Object Detection in the Real World

arXiv 2108.11005 ↗First posted 25 Aug 2021cs.CV cs.LGcited by 34

Not on the map. Why?

Abstract (arXiv)

Online continual learning from data streams in dynamic environments is a critical direction in the computer vision field. However, realistic benchmarks and fundamental studies in this line are still missing. To bridge the gap, we present a new online continual object detection benchmark with an egocentric video dataset, Objects Around Krishna (OAK). OAK adopts the KrishnaCAM videos, an ego-centric video stream collected over nine months by a graduate student. OAK provides exhaustive bounding box annotations of 80 video snippets (~17.5 hours) for 105 object categories in outdoor scenes. The emergence of new object categories in our benchmark follows a pattern similar to what a single person might see in their day-to-day life. The dataset also captures the natural distribution shifts as the person travels to different places. These egocentric long-running videos provide a realistic playground for continual learning algorithms, especially in online embodied settings. We also introduce new evaluation metrics to evaluate the model performance and catastrophic forgetting and provide baseline studies for online continual object detection. We believe this benchmark will pose new exciting challenges for learning from non-stationary data in continual learning. The OAK dataset and the associated benchmark are released at https://oakdata.github.io/.

Key facts. Cited by 34 papers in the map (data through 7 Oct 2026). Builds on 35 of its 49 references that are in the map. First posted on arXiv 25 Aug 2021.

Builds on

35 of 49 references.

References · 35

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  3. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,267
  4. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
  5. 2020End-to-End Object Detection with Transformerscited by 7,384
  6. 2017Mask R-CNNcited by 7,259
  7. 2016Overcoming catastrophic forgetting in neural networkscited by 4,718
  8. 2016Learning without Forgettingcited by 2,465
  9. 2016iCaRL: Incremental Classifier and Representation Learningcited by 2,313
  10. 2017Gradient Episodic Memory for Continual Learningcited by 1,871
  11. 2018Continual Lifelong Learning with Neural Networks: A Reviewcited by 1,313
  12. 2019LVIS: A Dataset for Large Vocabulary Instance Segmentationcited by 1,215
23 more
  1. 2017Memory Aware Synapses: Learning what (not) to forgetcited by 1,094
  2. 2018Scaling Egocentric Vision: The EPIC-KITCHENS Datasetcited by 789
  3. 2013An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networkscited by 711
  4. 2017Lifelong Learning with Dynamically Expandable Networkscited by 689
  5. 2018Progress & Compress: A scalable framework for continual learningcited by 516
  6. 2019Online Continual Learning with Maximally Interfered Retrievalcited by 376
  7. 2017CORe50: a New Dataset and Benchmark for Continuous Object Recognitioncited by 287
  8. 2020Frustratingly Simple Few-Shot Object Detectioncited by 280
  9. 2018Few-shot Object Detection via Feature Reweightingcited by 265
  10. 2018Task-Free Continual Learningcited by 219
  11. 2017Incremental Learning of Object Detectors without Catastrophic Forgettingcited by 208
  12. 2019Meta-Learning Representations for Continual Learningcited by 189
  13. 2018Reinforced Continual Learningcited by 186
  14. 2020A Neural Dirichlet Process Mixture Model for Task-Free Continual Learningcited by 133
  15. 2020Incremental Few-Shot Object Detectioncited by 102
  16. 2019Ego-Pose Estimation and Forecasting as Real-Time PD Controlcited by 87
  17. 2016A Survey on Object Detection in Optical Remote Sensing Imagescited by 78
  18. 2020Online Continual Learning under Extreme Memory Constraintscited by 48
  19. 2020Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learningcited by 38
  20. 2020Lifelong Object Detectioncited by 25
  21. 2020Wandering Within a World: Online Contextualized Few-Shot Learningcited by 22
  22. 2019Egocentric Hand Track and Object-based Human Action Recognitioncited by 12
  23. 2019Continual egocentric object recognitioncited by 12

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 7; 2023: 12; 2024: 7; 2025: 5; 2026: 2.

34 papers.

Sort:

By area:

  1. 2023A Comprehensive Survey of Continual Learning: Theory, Method and Applicationcited by 860
  2. 2023Class-Incremental Learning: A Surveycited by 209
  3. 2023An Outlook into the Future of Egocentric Visioncited by 84
  4. 2022UC-OWOD: Unknown-Classified Open World Object Detectioncited by 40
  5. 2023TiC-CLIP: Continual Training of CLIP Modelscited by 38
  6. 2021CORA: Benchmarks, Baselines, and Metrics as a Platform for Continual Reinforcement Learning Agentscited by 36
  7. 2022CLAD: A realistic Continual Learning benchmark for Autonomous Drivingcited by 35
  8. 2024AIDE: An Automatic Data Engine for Object Detection in Autonomous Drivingcited by 26
  9. 2022Continual Object Detection: A review of definitions, strategies, and challengescited by 25
  10. 2024A Practitioner's Guide to Continual Multimodal Pretrainingcited by 22
  11. 2023Streaming Active Learning with Deep Neural Networkscited by 20
  12. 2024Coreset Selection for Object Detectioncited by 18
22 more
  1. 2022Label-Efficient Online Continual Object Detection in Streaming Videocited by 16
  2. 2023Inherit with Distillation and Evolve with Contrast: Exploring Class Incremental Semantic Segmentation Without Exemplar Memorycited by 12
  3. 2023Balanced Destruction-Reconstruction Dynamics for Memory-replay Class Incremental Learningcited by 10
  4. 2022Improving Replay-Based Continual Semantic Segmentation with Smart Data Selectioncited by 8
  5. 2022Bridging Images and Videos: A Simple Learning Framework for Large Vocabulary Video Object Detectioncited by 6
  6. 2023Preserving Linear Separability in Continual Learning by Backward Feature Projectioncited by 6
  7. 2023Adaptive Visual Scene Understanding: Incremental Scene Graph Generationcited by 6
  8. 2024Reawakening knowledge: Anticipatory recovery from catastrophic interference via structured trainingcited by 6
  9. 2025Memory Storyboard: Leveraging Temporal Segmentation for Streaming Self-Supervised Learning from Egocentric Videoscited by 6
  10. 2025RICO: Two Realistic Benchmarks and an In-Depth Analysis for Incremental Learning in Object Detectioncited by 5
  11. 2023Predicting Class Distribution Shift for Reliable Domain Adaptive Object Detectioncited by 4
  12. 2026Elastic Weight Consolidation Done Right for Continual Learningcited by 3
  13. 2024BSDP: Brain-inspired Streaming Dual-level Perturbations for Online Open World Object Detectioncited by 2
  14. 2024Center-Sensitive Kernel Optimization for Efficient On-Device Incremental Learningcited by 2
  15. 2024TiROD: Tiny Robotics Dataset and Benchmark for Continual Object Detectioncited by 2
  16. 2025Hierarchical Visual Prompt Learning for Continual Video Instance Segmentationcited by 2
  17. 2023Dynamic Y-KD: A Hybrid Approach to Continual Instance Segmentationcited by 1
  18. 2023EgoAdapt: A multi-stream evaluation study of adaptation to real-world egocentric user videocited by 1
  19. 2025Ranking-aware Continual Learning for LiDAR Place Recognitioncited by 1
  20. 2025CRAM: Large-scale Video Continual Learning with Bootstrapped Compressioncited by 1
  21. 2026Learning on the Fly: Replay-Based Continual Object Perception for Indoor Dronescited by 1
  22. 2022Recent Trends in 2D Object Detection and Applications in Video Event Recognitioncited by 0