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

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

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

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

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

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

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

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

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

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

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

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