mlsanityData to 14 Oct 2026

Multiscale Domain Adaptive YOLO for Cross-Domain Object Detection

arXiv 2106.01483 ↗First posted 2 Jun 2021cs.CVcited by 23

Not on the map. Why?

Abstract (arXiv)

The area of domain adaptation has been instrumental in addressing the domain shift problem encountered by many applications. This problem arises due to the difference between the distributions of source data used for training in comparison with target data used during realistic testing scenarios. In this paper, we introduce a novel MultiScale Domain Adaptive YOLO (MS-DAYOLO) framework that employs multiple domain adaptation paths and corresponding domain classifiers at different scales of the recently introduced YOLOv4 object detector to generate domain-invariant features. We train and test our proposed method using popular datasets. Our experiments show significant improvements in object detection performance when training YOLOv4 using the proposed MS-DAYOLO and when tested on target data representing challenging weather conditions for autonomous driving applications.

Key facts. Cited by 23 papers in the map (data through 14 Oct 2026). Builds on 17 of its 24 references that are in the map. First posted on arXiv 2 Jun 2021.

Builds on

17 of 24 references.

References · 17

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,639
  3. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,852
  4. 2016The Cityscapes Dataset for Semantic Urban Scene Understandingcited by 4,444
  5. 2015SSD: Single Shot MultiBox Detectorcited by 3,130
  6. 2015Domain-Adversarial Training of Neural Networkscited by 3,044
  7. 2014Unsupervised Domain Adaptation by Backpropagationcited by 1,917
  8. 2020YOLOv4: Optimal Speed and Accuracy of Object Detectioncited by 1,630
  9. 2017Adversarial Discriminative Domain Adaptationcited by 1,311
  10. 2018Domain Adaptive Faster R-CNN for Object Detection in the Wildcited by 443
  11. 2017Semantic Foggy Scene Understanding with Synthetic Datacited by 403
  12. 2016Unsupervised Domain Adaptation with Residual Transfer Networkscited by 341
5 more
  1. 2018Strong-Weak Distribution Alignment for Adaptive Object Detectioncited by 270
  2. 2019Multi-adversarial Faster-RCNN for Unrestricted Object Detectioncited by 112
  3. 2019Few-shot Adaptive Faster R-CNNcited by 42
  4. 2019Towards Instance-level Image-to-Image Translationcited by 36
  5. 2020Deep Domain Adaptive Object Detection: a Surveycited by 20

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 3; 2022: 6; 2023: 2; 2024: 8; 2025: 0; 2026: 4.

23 papers.

Sort:

By area:

  1. 2021Image-Adaptive YOLO for Object Detection in Adverse Weather Conditionscited by 85
  2. 2021Domain Adaptive YOLO for One-Stage Cross-Domain Detectioncited by 23
  3. 2023FeatEnHancer: Enhancing Hierarchical Features for Object Detection and Beyond Under Low-Light Visioncited by 22
  4. 2022SSDA-YOLO: Semi-supervised Domain Adaptive YOLO for Cross-Domain Object Detectioncited by 21
  5. 2022GDIP: Gated Differentiable Image Processing for Object-Detection in Adverse Conditionscited by 20
  6. 2022Efficient Visual Computing with Camera RAW Snapshotscited by 18
  7. 2024HazyDet: Open-Source Benchmark for Drone-View Object Detection with Depth-Cues in Hazy Scenescited by 15
  8. 2022TogetherNet: Bridging Image Restoration and Object Detection Together via Dynamic Enhancement Learningcited by 10
  9. 2024Source-Free Domain Adaptation for YOLO Object Detectioncited by 9
  10. 2022Integrated Multiscale Domain Adaptive YOLOcited by 8
  11. 2024ERUP-YOLO: Enhancing Object Detection Robustness for Adverse Weather Condition by Unified Image-Adaptive Processingcited by 8
  12. 2022CF-YOLO: Cross Fusion YOLO for Object Detection in Adverse Weather with a High-quality Real Snow Datasetcited by 7
11 more
  1. 2024Versatile Teacher: A Class-aware Teacher-student Framework for Cross-domain Adaptationcited by 4
  2. 2021RiWNet: A moving object instance segmentation Network being Robust in adverse Weather conditionscited by 2
  3. 2024D-YOLO a robust framework for object detection in adverse weather conditionscited by 2
  4. 2023DisPlacing Objects: Improving Dynamic Vehicle Detection via Visual Place Recognition under Adverse Conditionscited by 1
  5. 2024CPA-Enhancer: Chain-of-Thought Prompted Adaptive Enhancer for Object Detection under Unknown Degradationscited by 1
  6. 2024FogGuard: guarding YOLO against fog using perceptual losscited by 0
  7. 2024SDNIA-YOLO: A Robust Object Detection Model for Extreme Weather Conditionscited by 0
  8. 2026MUSDA: Multi-source Multi-modality Unsupervised Domain Adaptive 3D Object Detection for Autonomous Drivingcited by 0
  9. 2026Dual-Integrated Low-Latency Single-Lens Infrared Computational Imaging for Object Detectioncited by 0
  10. 2026FR-DETR: Frequency and Recurrent Feature Refinement for Robust Object Detection under Adverse Weathercited by 0
  11. 2026JMT-YOLO: Multi-task Domain Adaptation via Segmentation-Guided Consistency Learningcited by 0