返回榜单
Eugene's AR Wiki: Play & Learn

Eugene's AR Wiki: Play & Learn

Bilal Mohamed

Entertainment免费v4.3
App Store
评分

4.7

502 条评分

星级

★★★★★

最近更新

2025年11月13日

发布日期

2019年1月8日

更新内容

v4.3

- Bug fixes

应用信息

开发者
Bilal Mohamed
分类
Entertainment
价格
免费
版本
4.3
App ID
1444525033

简介

Eugene’s AR Wiki: Play & Learn – Augmented Reality, Learning & Adventure! Step into a world where learning, playing, and exploring come alive right before your eyes. Eugene’s AR Wiki: Play & Learn invites you to discover lifelike AR animals, dinosaurs, and educational models, dive into a fascinating knowledge-packed wiki, and challenge yourself with engaging word games. Whether you're at home, outside, or on the go, every setting becomes an interactive playground of discovery. 3 Main Categories to Explore: 1. 3D Models (AR Animals & More) Bring virtual creatures and objects to life - from farm animals and wild animals, to dinosaurs, birds, sea creatures, insects, and science models. Walk around them, engage with animations, and capture stunning photos and videos to share. 2. Wiki (Educational Content) Unlock fascinating facts about each animal or object. From domestic pets and exotic wildlife to prehistoric giants - each model includes informative details to play and learn. 3. Games (Word Games) Enjoy brain-boosting fun with mini-games like Word Guess, 1 Pic – 4 Words, and 4 Words – 1 Pic. Great for kids, families, or solo puzzle fans. Why You’ll Love Eugene’s AR Wiki: Play & Learn: 1. Explore a massive collection of AR animals and 3D models with realistic movement and scale. 2. Learn fascinating facts from the built-in interactive Wiki. 3. Play addictive word games to sharpen your brain. 4. Use camera filters to snap memorable photos and videos with virtual creatures. 5. Suitable for all ages - infants, kids and adults alike. Whether you're walking with a dinosaur, discovering your spirit animal, or solving word puzzles, Eugene’s AR Wiki: Play & Learn delivers an enriching blend of education and entertainment.

下载量预测

专业 · 预览

预估总下载量

37K25K72K
保守估计乐观估计

279

低 / 月

413

预估 / 月

797

高 / 月

基于502 条评分
假设评分率1.4%
应用年龄90 个月

基于评分数量 ÷ 类别评分率估算,实际下载量误差可达 ±50%,与 Sensor Tower 方法一致。