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xavierpuigf/virtualhome

默认分支 master · commit 58970fd8 · 扫描时间 2026/6/15 17:31:47

星标 618 · Fork 90

AI 可见性总分
68 /100
需要改进
品类召回
1 / 2
被推荐时的平均排名 #3.0
规则结果
通过 2 · 警告 0 · 失败 0
客观元数据检查
AI 认识你的名字
3 / 3
直接询问时,AI 是否点名你的仓库
如何阅读这份报告

行动计划告诉你下一步要做什么——按影响力排序、可直接复制粘贴的修改。品类可见性是真正的 GEO 测试:当用户向 AI 提一个不带品牌、本应让 xavierpuigf/virtualhome 浮出水面的问题时,AI 是真的推荐了你,还是推荐了你的竞品?客观检查验证 AI 引擎最先权衡的那些元数据信号。自指检查判断 AI 是否还认识你的名字。

行动计划 — 可复制粘贴的修复

3 条由 gemini-2.5-flash 生成、按优先级排序的修改。修完后请把对应条目标记为完成。

整体方向
  • highreadme#1
    Reposition README opening to emphasize synthetic data generation

    原因:

    当前
    VirtualHome is an interactive platform to simulate complex household activities via programs. Key aspect of VirtualHome is that it allows complex interactions with the environment, such as picking up objects, switching on/off appliances, opening appliances, etc. Our simulator can easily be called with a Python API: write the activity as a simple sequence of instructions which then get rendered in VirtualHome. You can choose between different agents and environments, as well as modify environments on the fly. You can also stream different ground-truth such as time-stamped actions, instance/semantic segmentation, and optical flow and depth. The platform allows to simulate multi-agent activities and can serve as an environment to train agents for embodied AI tasks.
    复制粘贴的修复
    **VirtualHome** is an interactive platform to simulate complex household activities via programs, serving as a robust environment for embodied AI research and **synthetic data generation**. It provides rich ground-truth data, including instance/semantic segmentation, optical flow, and depth, alongside its core capability for complex interactions with the environment (picking up objects, switching appliances). Our simulator, easily called with a Python API, allows writing activities as simple instruction sequences, rendered in VirtualHome, and supports multi-agent activities and dynamic environment modification.
  • mediumtopics#2
    Add specific topics for synthetic data and embodied AI

    原因:

    当前
    computer-vision, deep-learning, graph, multi-agent, reinforcement-learning, simulator, unity
    复制粘贴的修复
    computer-vision, deep-learning, graph, multi-agent, reinforcement-learning, simulator, unity, synthetic-data, data-generation, segmentation, depth-estimation, embodied-ai
  • lowreadme#3
    Add a 'Key Capabilities' section to the README

    原因:

    复制粘贴的修复
    ## Key Capabilities
    
    *   **Programmatic Control:** Define complex household activities via a simple Python API.
    *   **Multi-Agent Simulation:** Support for multiple AI agents interacting within the environment.
    *   **Rich Ground-Truth Data:** Stream instance/semantic segmentation, optical flow, and depth for synthetic data generation.
    *   **Interactive Environments:** Agents can pick up objects, switch appliances, open/close containers, and modify environments dynamically.
    *   **Procedural Generation:** Create infinite unique environments for diverse training scenarios.
    *   **Embodied AI Training:** An ideal environment for training agents in complex embodied AI tasks.

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

品类可见性 — 真正的 GEO 测试

向 google/gemini-2.5-flash 提出的不带品牌问题。AI 推荐了你,还是推荐了别人?

各模型使用同一组问题 — 切换标签对比回答与排名。

召回
1 / 2
50% 的问题里出现了 xavierpuigf/virtualhome
平均排名
#3.0
越小越好。#1 表示首位推荐。
声量占比
8%
在所有被点名的工具中,你占了多少?
头号对手
AI2-THOR
在 2 个问题中被推荐 1 次
竞品排行
  1. AI2-THOR · 被推荐 1 次
  2. Habitat · 被推荐 1 次
  3. iGibson · 被推荐 1 次
  4. MINERVA · 被推荐 1 次
  5. NVIDIA Isaac Sim · 被推荐 1 次
  • 品类问题
    What simulation environments support training multiple AI agents in interactive household settings?
    你:第 3 位
    AI 推荐顺序:
    1. AI2-THOR
    2. Habitat
    3. VirtualHome ← 你
    4. iGibson
    5. MINERVA
    查看 AI 完整回答
  • 品类问题
    Looking for a simulator to generate synthetic data for embodied AI, including segmentation and depth.
    你:未被推荐
    AI 推荐顺序:
    1. NVIDIA Isaac Sim
    2. Unity 3D
    3. Perception Package
    4. Unreal Engine
    5. AirSim
    6. CARLA
    7. Habitat-Sim
    8. Gazebo

    AI 推荐了 8 个替代方案,却始终没点名 xavierpuigf/virtualhome。这就是要补上的差距。

    查看 AI 完整回答

客观检查

针对 AI 引擎最看重的元数据信号的规则审计。

  • Metadata completeness
    pass

  • README presence
    pass

自指检查

当被直接问到你时,AI 是否还知道你的仓库存在?

  • Compared to common alternatives in this category, what is the core differentiator of xavierpuigf/virtualhome?
    pass
    AI 明确点名了 xavierpuigf/virtualhome

    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 xavierpuigf/virtualhome in production, what risks or prerequisites should they evaluate first?
    pass
    AI 明确点名了 xavierpuigf/virtualhome

    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 xavierpuigf/virtualhome solve, and who is the primary audience?
    pass
    AI 明确点名了 xavierpuigf/virtualhome

    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?

嵌入你的 GEO 徽章

把这个徽章贴进 xavierpuigf/virtualhome 的 README。每次重新扫描都会自动更新,并跳到最新报告——是「我在乎 AI 可发现性」最简单的公开证明。

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订阅 Pro,解锁深度诊断

xavierpuigf/virtualhome — 轻量扫描仍免费;本卡列出 Pro 相对轻量的深度额度。

  • 深度报告每月 10 次
  • 无品牌品类查询5,轻量 2
  • 优先行动项8,轻量 3