REPOGEO REPORT · LITE
leoxiaobin/deep-high-resolution-net.pytorch
Default branch master · commit 6f69e467 · scanned 6/28/2026, 6:13:01 PM
GitHub: 4,478 stars · 923 forks
Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.
2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).
Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface leoxiaobin/deep-high-resolution-net.pytorch, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.
Action plan — copy-paste fixes
3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- highreadme#1Reposition the core identity statement to the top of the README
Why:
COPY-PASTE FIXAdd the following sentence directly under the main title (H1): "This repository provides the official PyTorch implementation of Deep High-Resolution Representation Learning for Human Pose Estimation (HRNet)."
- mediumtopics#2Add more specific topics to clarify its role as a model implementation
Why:
CURRENTcoco-keypoints-detection, deep-high-resolution-net, deep-learning, high-resolution-net, human-pose-estimation, mpii, mpii-dataset, mscoco-keypoint
COPY-PASTE FIXcoco-keypoints-detection, deep-high-resolution-net, deep-learning, high-resolution-net, human-pose-estimation, mpii, mpii-dataset, mscoco-keypoint, pytorch-implementation, human-pose-estimation-model
- lowreadme#3Add a concise 'What is HRNet?' section to the README
Why:
COPY-PASTE FIXAdd a new section, perhaps titled 'What is HRNet?' or 'Key Features', with text like: 'HRNet maintains high-resolution representations throughout the entire network by connecting high-to-low resolution convolutions in parallel and repeatedly exchanging information across resolutions.'
Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash
Category visibility — the real GEO test
Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?
Same questions for every model — switch tabs to compare answers and rankings.
- Detectron2 · recommended 2×
- AlphaPose · recommended 1×
- HRNet · recommended 1×
- ViTPose · recommended 1×
- OpenPose · recommended 1×
- CATEGORY QUERYWhat are state-of-the-art deep learning methods for precise human pose estimation?you: not recommendedAI recommended (in order):
- AlphaPose
- HRNet
- ViTPose
- OpenPose
- MediaPipe Pose
- Detectron2
- MMPose
AI recommended 7 alternatives but never named leoxiaobin/deep-high-resolution-net.pytorch. This is the gap to close.
Show full AI answer
- CATEGORY QUERYSeeking deep learning frameworks for high-resolution image analysis and keypoint detection.you: not recommendedAI recommended (in order):
- PyTorch
- TensorFlow
- Detectron2
- MMDetection
- MXNet
- JAX
AI recommended 6 alternatives but never named leoxiaobin/deep-high-resolution-net.pytorch. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesspass
- README presencepass
Self-mention check
Does AI even know your repo exists when asked about it directly?
- Compared to common alternatives in this category, what is the core differentiator of leoxiaobin/deep-high-resolution-net.pytorch?passAI did not name leoxiaobin/deep-high-resolution-net.pytorch — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts leoxiaobin/deep-high-resolution-net.pytorch in production, what risks or prerequisites should they evaluate first?passAI named leoxiaobin/deep-high-resolution-net.pytorch explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- In one sentence, what problem does the repo leoxiaobin/deep-high-resolution-net.pytorch solve, and who is the primary audience?passAI did not name leoxiaobin/deep-high-resolution-net.pytorch — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
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leoxiaobin/deep-high-resolution-net.pytorch — Lite scans stay free; this card itemizes Pro deep limits vs Lite.
- Deep reports10 / month
- Brand-free category queries5 vs 2 in Lite
- Prioritized action items8 vs 3 in Lite