Ngā tūemi rite

• DiverGen: Improving Instance Segmentation by Learning Wider Data Distribution with More Diverse Generative Data
  mā: Fan, Chengxiang, me ētahi atu.
  I whakaputaina: (2024)
• Matcher: Segment Anything with One Shot Using All-Purpose Feature Matching
  mā: Liu, Yang, me ētahi atu.
  I whakaputaina: (2023)
• A Simple Image Segmentation Framework via In-Context Examples
  mā: Liu, Yang, me ētahi atu.
  I whakaputaina: (2024)
• Unleashing the Potential of the Diffusion Model in Few-shot Semantic Segmentation
  mā: Zhu, Muzhi, me ētahi atu.
  I whakaputaina: (2024)
• Where to Look: Can Foundation Models Reach a Target Viewpoint Through Active Exploration?
  mā: Li, Liyang, me ētahi atu.
  I whakaputaina: (2026)