gem-x.cpp
Track live or prerecorded humanoid movements to produce a 3D skeleton. C++/GGML conversion of NVIDIA's GEM-X
Details
- External ID
- 1379553159
- Source
- GITHUB
- Company
- —
- Product
- gem-x.cpp
- Website domain
- github.com
- Launched
- Sept. 21, 2026
- Cohort
- —
- Upvotes
- 29
- Upvotes percentile
- 0.7161798616448886
- Tags
- —
- Fetched at
- Sept. 25, 2026, 5:02 p.m.
- Updated at
- Sept. 25, 2026, 5:02 p.m.
Enrichment
- Theme
- creative coding and visual experiments
- Vertical
- Media & entertainment
- Function
- Model & infra
- Audience
- Developer
- AI stance
- AI-native
- Project type
- Hobby / open-source project
- Normalized one-liner
- c++ and ggml port of nvidia's gem-x 3d skeleton tracking
- Manually corrected
- False
Could you build this?
No Porting a complex deep-learning computer vision architecture (NVIDIA GEM-X) to raw C++ using GGML requires high-level mathematical expertise, deep tensor library knowledge, and low-level model architecture reimplementation.
What it would actually take: Building gem-x.cpp requires reverse engineering or inspecting NVIDIA's PyTorch/TensorRT model architecture, extracting weights, and re-implementing custom neural operators in C++ on top of GGML/llama.cpp-style compute graphs. The hard part is quantizing weights, handling 3D skeleton pose regression tensor math manually, and optimizing SIMD/CUDA kernels for real-time tracking, demanding deep expertise in machine learning systems engineering and low-level C++ performance optimization.
Competitors
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Attention rank: #205 of 715 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).
Launched 324 days after the earliest competitor.
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Other launches for this product
- No other launches for this product.
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