REPOGEO REPORT · LITE

leoxiaobin/deep-high-resolution-net.pytorch

Default branch master · commit 6f69e467 · scanned 5/17/2026, 1:42:49 PM

GitHub: 4,473 stars · 925 forks

Scan history for this repo

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.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE

27 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

2 pass · 0 warn · 0 fail

Objective metadata checks

AI knows your name

1 / 3

Direct prompts that named your repo

HOW TO READ THIS REPORT

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.

OVERALL DIRECTION

highreadme#1

Emphasize 'HRNet' and 'official PyTorch implementation' in the README's first sentence

Why:

CURRENT

This is an official pytorch implementation of *Deep High-Resolution Representation Learning for Human Pose Estimation*.

COPY-PASTE FIX

This is the official PyTorch implementation of Deep High-Resolution Representation Learning for Human Pose Estimation (HRNet).

mediumtopics#2

Add 'pytorch' and 'cvpr-2019' to the repository topics

Why:

CURRENT

coco-keypoints-detection, deep-high-resolution-net, deep-learning, high-resolution-net, human-pose-estimation, mpii, mpii-dataset, mscoco-keypoint

COPY-PASTE FIX

coco-keypoints-detection, deep-high-resolution-net, deep-learning, high-resolution-net, human-pose-estimation, mpii, mpii-dataset, mscoco-keypoint, pytorch, cvpr-2019

lowreadme#3

Add a clear link to the official project homepage in the README's introduction

Why:

COPY-PASTE FIX

The official project page for HRNet human pose estimation can be found [here](https://jingdongwang2017.github.io/Projects/HRNet/PoseEstimation.html).

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.

Recall

0 / 2

0% of queries surface leoxiaobin/deep-high-resolution-net.pytorch

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

YOLO-Pose

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

YOLO-Pose · recommended 2×
HRNet · recommended 1×
AlphaPose · recommended 1×
ViTPose · recommended 1×
OpenPose · recommended 1×

CATEGORY QUERY
What are the best deep learning models for high-resolution human pose estimation?
you: not recommended
AI recommended (in order):
1. HRNet
2. AlphaPose
3. ViTPose
4. OpenPose
5. DEKR
6. YOLO-Pose
7. HigherHRNet
AI recommended 7 alternatives but never named leoxiaobin/deep-high-resolution-net.pytorch. This is the gap to close.
Show full AI answer
CATEGORY QUERY
How can I achieve accurate keypoint detection for human figures in images?
you: not recommended
AI recommended (in order):
1. MediaPipe Pose (google/mediapipe)
2. OpenPose (CMU-Perceptual-Computing-Lab/openpose)
3. AlphaPose (MVIG-SJTU/AlphaPose)
4. HRNet (HRNet/HRNet-Pose-Estimation)
5. Detectron2 (facebookresearch/detectron2)
6. YOLO-Pose
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 completeness
pass
README presence
pass

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?
pass
AI 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?
pass
AI 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?
pass
AI 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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Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite