Illustration of feature matching of UFM. When working with specific data, the pre-trained backbone is frozen, and only the corresponding modal assistants need to be fine-tuned for feature matching. The multi-modal assistants contain both same-modal assistants and different-modal matching assistants.

مواد مشابهة

• Fine-tuning on same-model feature matching tasks. The X-FFN and Y-FFN represent the assistants of any two kinds of pre-trained different modal images in the second stage of Fig 4. The fine-tuning of the X-modal image and the fine-tuning of the Y-modal image are independent of each other.
  حسب: Yide Di (20969124)
  منشور في: (2025)
• Feature matching of same-modal images. (a) SuperGlue (b) MatchFomer (c) LoFTR (d) UFM. The matches with less than 1 pixel error are represented by lines.
  حسب: Yide Di (20969124)
  منشور في: (2025)
• Fine-tuning on different-model feature matching tasks. The X-FFN and Y-FFN represent the assistants of any two kinds of pre-trained different modal images in the second stage of Fig 4. The X-Y FFN represent the assistant of the pre-trained different modal images in the third stage of Fig 4.
  حسب: Yide Di (20969124)
  منشور في: (2025)
• The overview of UFM and the MIA transformer. The UFM model encompasses all the processes involved in image enhancement, feature extraction, coarse matching, and fine matching. The MIA Transformer is utilized in both the coarse and fine matching stages.
  حسب: Yide Di (20969124)
  منشور في: (2025)
• MMA estimation on multi-modal images in SEN12MS dataset.
  حسب: Yide Di (20969124)
  منشور في: (2025)