dk-liang/Awesome-Visual-Transformer

• highreadme#1

  Clarify repo's nature as a curated list in README opening

  原因：

  当前

  Collect some Transformer with Computer-Vision (CV) papers.

  复制粘贴的修复

  复制

  This is a curated "awesome list" collecting key research papers, code, and resources on Transformers applied to Computer Vision (CV).

  待办完成忽略
• highlicense#2

  Add a LICENSE file to the repository

  原因：

  当前

  (no LICENSE file detected — the repo has no recognizable license)

  复制粘贴的修复

  复制

  Choose and add a standard open-source license file (e.g., MIT, Apache-2.0, GPL-3.0) to the repository root.

  待办完成忽略
• mediumhomepage#3

  Add a homepage URL to the repository settings

  原因：

  复制粘贴的修复

  复制

  Set the repository homepage URL to a relevant link, such as the GitHub repository URL itself (https://github.com/dk-liang/Awesome-Visual-Transformer) or a dedicated project page if one exists.

  待办完成忽略

本次扫描解析到的品类 GEO 通道：google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• 品类问题

  Where can I find a comprehensive collection of research papers on visual transformers?

  你：未被推荐
  AI 推荐顺序：

  1. arXiv.org
  2. Google Scholar
  3. Papers With Code
  4. Semantic Scholar
  5. IEEE Xplore Digital Library
  6. ACM Digital Library
  7. OpenReview.net

  AI 推荐了 7 个替代方案，却始终没点名 dk-liang/Awesome-Visual-Transformer。这就是要补上的差距。

  查看 AI 完整回答
• 品类问题

  What are the latest advancements and surveys in applying transformers to computer vision tasks?

  你：未被推荐
  AI 推荐顺序：

  1. Vision Transformers (ViT)
  2. DeiT (Data-efficient Image Transformers)
  3. Swin Transformer
  4. PVT (Pyramid Vision Transformer)
  5. DETR (DEtection TRansformer)
  6. Deformable DETR
  7. DINO (DETR with Improved deNoising anchOr boxes)
  8. Mask2Former
  9. SegFormer
  10. ViViT (Video Vision Transformer)
  11. MViT (Multiscale Vision Transformers)
  12. MAE (Masked Autoencoders Are Scalable Vision Learners)
  13. DINO (Emerging Properties in Self-Supervised Vision Transformers)

  AI 推荐了 13 个替代方案，却始终没点名 dk-liang/Awesome-Visual-Transformer。这就是要补上的差距。

  查看 AI 完整回答

• Metadata completeness

  warn

  建议：

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of dk-liang/Awesome-Visual-Transformer?

  pass
  ✓AI 明确点名了 dk-liang/Awesome-Visual-Transformer

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• If a team adopts dk-liang/Awesome-Visual-Transformer in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI 明确点名了 dk-liang/Awesome-Visual-Transformer

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• In one sentence, what problem does the repo dk-liang/Awesome-Visual-Transformer solve, and who is the primary audience?

  pass
  ⚠AI 未点名 dk-liang/Awesome-Visual-Transformer —— 很可能在说另一个项目

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？