# Source Registry ## Source #1 - **Title**: LiteSAM GitHub Repository - **Link**: https://github.com/boyagesmile/LiteSAM - **Tier**: L1 - **Publication Date**: 2025-10-01 - **Timeliness Status**: ✅ Currently valid - **Version Info**: 4 commits total, no releases, no license - **Target Audience**: Computer vision researchers, satellite-aerial matching - **Research Boundary Match**: ✅ Full match - **Summary**: Official LiteSAM code repo. 5 stars, 0 forks, no issues. Weights hosted on Google Drive (mloftr.ckpt). Built on EfficientLoFTR. Very low community adoption. - **Related Sub-question**: SQ-2, SQ-3 ## Source #2 - **Title**: LiteSAM Paper (Remote Sensing, MDPI) - **Link**: https://www.mdpi.com/2072-4292/17/19/3349 - **Tier**: L1 - **Publication Date**: 2025-10-01 - **Timeliness Status**: ✅ Currently valid - **Version Info**: Remote Sensing Vol 17, Issue 19 - **Target Audience**: Remote sensing, UAV localization researchers - **Research Boundary Match**: ✅ Full match - **Summary**: 6.31M params. 77.3% Hard hit rate is on SELF-MADE dataset (Harbin/Qiqihar), NOT UAV-VisLoc. UAV-VisLoc Hard: 61.65%, RMSE@30=17.86m. Benchmarked on RTX 3090. - **Related Sub-question**: SQ-2, SQ-3 ## Source #3 - **Title**: XFeat (CVPR 2024) - **Link**: https://github.com/verlab/accelerated_features - **Tier**: L1 - **Publication Date**: 2024-06-01 - **Timeliness Status**: ✅ Currently valid - **Version Info**: CVPR 2024, actively maintained - **Target Audience**: Feature extraction/matching community - **Research Boundary Match**: ✅ Full match - **Summary**: 5x faster than SuperPoint. AUC@10° 65.4 vs SuperPoint 50.1 on Megadepth. Built-in semi-dense matcher. ~15ms GPU, ~37ms CPU. - **Related Sub-question**: SQ-1 ## Source #4 - **Title**: SatLoc-Fusion (MDPI 2025) - **Link**: https://www.mdpi.com/2072-4292/17/17/3048 - **Tier**: L1 - **Publication Date**: 2025-08-01 - **Timeliness Status**: ✅ Currently valid - **Version Info**: Remote Sensing, 2025 - **Target Audience**: UAV navigation researchers - **Research Boundary Match**: ✅ Full match - **Summary**: Uses XFeat for VO + DINOv2 for satellite matching. <15m error, >90% trajectory coverage, >2Hz on 6 TFLOPS edge hardware. Validates XFeat for UAV VO. - **Related Sub-question**: SQ-1 ## Source #5 - **Title**: CVE-2025-32434 (PyTorch) - **Link**: https://nvd.nist.gov/vuln/detail/CVE-2025-32434 - **Tier**: L1 - **Publication Date**: 2025-04-01 - **Timeliness Status**: ✅ Currently valid - **Version Info**: PyTorch ≤2.5.1 - **Target Audience**: All PyTorch users - **Research Boundary Match**: ✅ Full match - **Summary**: RCE even with weights_only=True in torch.load(). Fixed in PyTorch 2.6+. - **Related Sub-question**: SQ-8 ## Source #6 - **Title**: CVE-2026-24747 (PyTorch) - **Link**: CVE database - **Tier**: L1 - **Publication Date**: 2026-01-01 - **Timeliness Status**: ✅ Currently valid - **Version Info**: Fixed in PyTorch 2.10.0+ - **Target Audience**: All PyTorch users - **Research Boundary Match**: ✅ Full match - **Summary**: Memory corruption in weights_only unpickler. Requires PyTorch ≥2.10.0. - **Related Sub-question**: SQ-8 ## Source #7 - **Title**: Nature Scientific Reports - DINOv2 ViT comparison - **Link**: https://www.nature.com/articles/s41598-024-83358-8 - **Tier**: L2 - **Publication Date**: 2024-12-01 - **Timeliness Status**: ✅ Currently valid - **Version Info**: 2024 - **Target Audience**: Computer vision researchers - **Research Boundary Match**: ⚠️ Partial overlap (classification, not retrieval) - **Summary**: ViT-S vs ViT-B: recall +2.54pp, precision +5.36pp. ViT-B uses ~900-1100MB VRAM vs ViT-S ~300MB. Not UAV-specific but indicative. - **Related Sub-question**: SQ-7 ## Source #8 - **Title**: Google Maps Ukraine Imagery Policy - **Link**: https://en.ain.ua/2024/05/10/google-maps-shows-mariupol-irpin-and-other-cities-destroyed-by-russia/ - **Tier**: L2 - **Publication Date**: 2024-05-10 - **Timeliness Status**: ✅ Currently valid - **Target Audience**: General public, geospatial users - **Research Boundary Match**: ✅ Full match - **Summary**: Google intentionally does not publish recent imagery of conflict areas. Imagery is 1-3 years old for eastern Ukraine. - **Related Sub-question**: SQ-10 ## Source #9 - **Title**: GTSAM IndeterminantLinearSystemException - **Link**: https://github.com/borglab/gtsam/issues/561 - **Tier**: L4 - **Publication Date**: 2021+ - **Timeliness Status**: ✅ Currently valid - **Version Info**: GTSAM 4.x - **Target Audience**: GTSAM users - **Research Boundary Match**: ✅ Full match - **Summary**: iSAM2.update() can throw IndeterminantLinearSystemException with certain factor patterns. Need error handling. - **Related Sub-question**: SQ-9 ## Source #10 - **Title**: EfficientLoFTR (CVPR 2024) - **Link**: https://github.com/zju3dv/EfficientLoFTR - **Tier**: L1 - **Publication Date**: 2024-06-01 - **Timeliness Status**: ✅ Currently valid - **Version Info**: 964 stars, CVPR 2024, HuggingFace integration - **Target Audience**: Feature matching community - **Research Boundary Match**: ✅ Full match - **Summary**: LiteSAM's base architecture. 15.05M params. Much more mature than LiteSAM. Has HuggingFace integration. Well-proven codebase. - **Related Sub-question**: SQ-3 ## Source #11 - **Title**: Tracasa SENX4 Ukraine Imagery - **Link**: https://tracasa.es/tracasa-offers-free-of-charge-500000-km2-of-super-resolved-sentinel-2-satellites-images-of-the-ukraine/ - **Tier**: L2 - **Publication Date**: 2022+ - **Timeliness Status**: ⚠️ Needs verification - **Version Info**: Super-resolved Sentinel-2 to 2.5m - **Target Audience**: Ukraine geospatial users - **Research Boundary Match**: ✅ Full match - **Summary**: Free 500,000 km² of Ukraine at 2.5m resolution (deep learning super-resolution from 10m Sentinel-2). Could serve as fallback. - **Related Sub-question**: SQ-10 ## Source #12 - **Title**: Maxar Ukraine Imagery Status - **Link**: https://en.defence-ua.com/news/maxar_satellite_imagery_is_still_available_in_ukraine_but_its_paid_only_now-13758.html - **Tier**: L3 - **Publication Date**: 2025-03-01 - **Timeliness Status**: ✅ Currently valid - **Summary**: Maxar restored Ukraine access March 2025 (was suspended). Paid-only. 31-50cm resolution. - **Related Sub-question**: SQ-10