REPOGEO REPORT · LITE

PKU-YuanGroup/MagicTime

Default branch main · commit 3b8f6bda · scanned 5/10/2026, 12:52:41 AM

GitHub: 1,342 stars · 123 forks

AI VISIBILITY SCORE

33 /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

2 / 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 PKU-YuanGroup/MagicTime, 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

Reposition README's opening paragraph to emphasize time-lapse

Why:

CURRENT

This repository is the official implementation of MagicTime, a metamorphic video generation pipeline based on the given prompts. The main idea is to enhance the capacity of video generation models to accurately depict the real world through our proposed methods and dataset.

COPY-PASTE FIX

This repository presents MagicTime, the official implementation of our novel approach to **time-lapse video generation**. MagicTime introduces **metamorphic simulators** to enhance video generation models, enabling them to accurately depict real-world temporal changes and long-term evolution from text prompts.

mediumtopics#2

Add more specific topics to differentiate from general video generation

Why:

CURRENT

diffusion-models, long-video-generation, metamorphic-video-generation, open-sora-plan, text-to-video, time-lapse, time-lapse-dataset, video-generation

COPY-PASTE FIX

diffusion-models, long-video-generation, metamorphic-video-generation, open-sora-plan, text-to-video, time-lapse, time-lapse-dataset, video-generation, **temporal-evolution**, **long-term-forecasting-video**, **dynamic-scene-synthesis**

mediumabout#3

Refine the 'About' description for clarity on metamorphic simulation

Why:

CURRENT

[TPAMI 2025🔥] MagicTime: Time-lapse Video Generation Models as Metamorphic Simulators

COPY-PASTE FIX

[TPAMI 2025🔥] MagicTime: Generate realistic **time-lapse videos** from text prompts using our novel **metamorphic simulation** approach.

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 PKU-YuanGroup/MagicTime

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

AnimateDiff

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

AnimateDiff · recommended 2×
Phenaki · recommended 2×
RunwayML (Gen-2) · recommended 1×
Pika Labs · recommended 1×
Stable Diffusion · recommended 1×

CATEGORY QUERY
How to generate realistic time-lapse videos from text descriptions using AI?
you: not recommended
AI recommended (in order):
1. RunwayML (Gen-2)
2. Pika Labs
3. Stable Diffusion
4. Deforum Stable Diffusion
5. AnimateDiff
6. Midjourney
7. DAIN-App
8. Flowframes
9. Adobe After Effects
10. Google Imagen Video
11. Phenaki
AI recommended 11 alternatives but never named PKU-YuanGroup/MagicTime. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are the best open-source models for generating long, evolving videos with diffusion?
you: not recommended
AI recommended (in order):
1. Stable Video Diffusion (SVD)
2. ControlNet
3. AnimateDiff
4. ModelScope Text-to-Video Synthesis (T2V)
5. VideoCrafter
6. Phenaki
AI recommended 6 alternatives but never named PKU-YuanGroup/MagicTime. 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 PKU-YuanGroup/MagicTime?
pass
AI did not name PKU-YuanGroup/MagicTime — 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 PKU-YuanGroup/MagicTime in production, what risks or prerequisites should they evaluate first?
pass
AI named PKU-YuanGroup/MagicTime 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 PKU-YuanGroup/MagicTime solve, and who is the primary audience?
pass
AI named PKU-YuanGroup/MagicTime explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

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MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/PKU-YuanGroup/MagicTime.svg)](https://repogeo.com/en/r/PKU-YuanGroup/MagicTime)

HTML

<a href="https://repogeo.com/en/r/PKU-YuanGroup/MagicTime"><img src="https://repogeo.com/badge/PKU-YuanGroup/MagicTime.svg" alt="RepoGEO" /></a>

Pro

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PKU-YuanGroup/MagicTime — 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