JMT-YOLO: Multi-task Domain Adaptation via Segmentation-Guided Consistency Learning

arXiv:2610.12901 · cs.CV · Submitted 2026-10-09 · Read on arXiv

cs.CV

Submitted: 2026-10-09

Updated: 2026-10-09

Code: https://github.com/25043221/JMT-YOLO

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Adaptation — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Domain Adaptation — 1× in this paper · explained in 5 episodes

Sources

• Deep Domain Confusion: Maximizing for Domain Invariance
• I3Net: Implicit Instance-Invariant Network for Adapting One-Stage Object Detectors
• Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
• SCL: Towards Accurate Domain Adaptive Object Detection via Gradient Detach Based Stacked Complementary Losses
• DA-Mamba: Domain Adaptive Hybrid Mamba-Transformer Based One-Stage Object Detection

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