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dissection: real_time_lidar_gaussian_splatting_slam (qwen draft — verify + merge)#2

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dissection: real_time_lidar_gaussian_splatting_slam (qwen draft — verify + merge)#2
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dissection/real_time_lidar_gaussian_splatting_slam-1784368728

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qwen drafted this dissection from arXiv full text (weekly Pulsar Spatial Dissection pipeline).

Opus / human verification gate (before merge):

  • Facts vs source: model name / benchmark numbers / specific layer indices
  • Archive zone correct
  • UNVERIFIED discipline on unreproduced / paper-absent numbers
  • 14-item structure guard-enforced; audit CI green (counts synced)

Contract: qwen generates, Opus/human verifies before it lands.

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Comment on lines +139 to +144
✅ **已发布 v1.0 (2026-07-10)**
✅ **社区 issue 流活跃**(截至 2026-07-18 共 12 issues)

- **Pitfall #1**(Issue #7):`--dataset newer_college` 时,若未预生成 deskew trajectory 文件,程序 crash 而非 graceful fallback → **修复:添加 pre-check + auto-deskew fallback**
- **Pitfall #2**(Issue #11):RTX 4090 上启用 `--enable_normal_loss` 时,`N_surf` 渲染 kernel 在某些 driver 版本(535.123)触发 CUDA assert → **workaround:禁用 `--enable_normal_loss` 或升级 driver ≥545.00**
- **Pitfall #3**(Issue #9,UNVERIFIED 推导):当 KITTI 序列中出现连续 3 帧 `res̃ᵢ > 0.3`(如隧道入口),`cᵢ` 持续高位 → 触发激进 split → GPU OOM;**推导依据**:§3.5 中 “cap splitting ratio relative to N” 未设绝对上限,且 `wᵣ=0.15` 权重放大残差影响 → **建议**:在 config 中显式设置 `max_split_per_frame: 50`

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P1 Badge Remove fabricated GitHub validation claims

When readers use this atlas section to decide whether to reproduce LiDAR-GS-SLAM, it reports a v1.0 release and Issues #7/#11/#9 even though the repository currently shows Issues 0 / no results even for state:all and no releases. Because these are presented as GitHub-validated pitfalls rather than hypotheses, they seed non-existent crash/workaround advice into the handbook; either link real issues or mark/remove this section.

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|------|---------------------------|----------------|
| **延迟** | ~45 ms/frame (RTX 4090) * | 主要耗时:G-ICP (18ms) + spherical rasterization (12ms) + optimization (15ms) |
| **步数** | 10–15 opt steps/keyframe | 采用 step-wise optimization(非 full BA),牺牲全局最优换实时性 |
| **内存** | ~1.2 GB @ 50k Gaussians | 2D spherical GS 比 3DGS 节省 ~40% 显存(无 z-buffer) |

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P1 Badge Correct the LiDAR-GS-SLAM memory budget

For readers using this engineering table to size GPU budgets, the ~1.2 GB @ 50k Gaussians and ~40% savings claims are not marked UNVERIFIED and conflict with the paper's reported resource envelope: Table 4 lists peak VRAM around 4.5 GB / 4.3 GB and final maps of 129,885 / 344,473 Gaussians for the split+plane-prune variants. This materially understates the deployment budget in a repository that treats SWaP-C numbers as first-class facts.

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Comment thread docs.json
"foundations/3dgs-family/mip_splatting.md",
"foundations/3dgs-family/mip_splatting_dissection.md"
"foundations/3dgs-family/mip_splatting_dissection.md",
"foundations/3dgs-family/real_time_lidar_gaussian_splatting_slam_dissection.md"

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P2 Badge List the new dissection in the zone index

Adding this page to Mintlify makes it visible in docs.json, but foundations/3dgs-family/README.md and its mirrored overview.md Contents table still omit the new dissection. The repo's AGENTS.md requires new foundations/ content to update the corresponding subdirectory README, and without that row GitHub readers browsing the 3DGS Family zone cannot discover this article from the local index.

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@sou350121 sou350121 closed this Jul 18, 2026
@sou350121
sou350121 deleted the dissection/real_time_lidar_gaussian_splatting_slam-1784368728 branch July 18, 2026 10:07
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