mlsanityData to 14 Oct 2026

Silver medal Solution for Image Matching Challenge 2024

arXiv 2411.01851 ↗First posted 4 Nov 2024cs.CV cs.AIcited by 0

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Abstract (arXiv)

Image Matching Challenge 2024 is a competition focused on building 3D maps from diverse image sets, requiring participants to solve fundamental computer vision challenges in image matching across varying angles, lighting, and seasonal changes. This project develops a Pipeline method that combines multiple advanced techniques: using pre-trained EfficientNet-B7 for initial feature extraction and cosine distance-based image pair filtering, employing both KeyNetAffNetHardNet and SuperPoint for keypoint feature extraction, utilizing AdaLAM and SuperGlue for keypoint matching, and finally applying Pycolmap for 3D spatial analysis. The methodology achieved an excellent score of 0.167 on the private leaderboard, with experimental results demonstrating that the combination of KeyNetAffNetHardNet and SuperPoint provides significant advantages in keypoint detection and matching, particularly when dealing with challenging variations in surface texture and environmental conditions that typically degrade traditional algorithm performance.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 19 of its 30 references that are in the map. First posted on arXiv 4 Nov 2024.

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19 of 30 references.

References · 19

  1. 2023DINOv2: Learning Robust Visual Features without Supervisioncited by 7,974
  2. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,585
  3. 2019EfficientNet: Rethinking Model Scaling for Convolutional Neural Networkscited by 6,442
  4. 2019SuperGlue: Learning Feature Matching with Graph Neural Networkscited by 1,443
  5. 2017SuperPoint: Self-Supervised Interest Point Detection and Descriptioncited by 1,320
  6. 2021Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNetcited by 1,101
  7. 2021LoFTR: Detector-Free Local Feature Matching with Transformerscited by 984
  8. 2015NetVLAD: CNN architecture for weakly supervised place recognitioncited by 941
  9. 2023EVA-CLIP: Improved Training Techniques for CLIP at Scalecited by 798
  10. 2023LightGlue: Local Feature Matching at Light Speedcited by 590
  11. 2021A Survey of Transformerscited by 401
  12. 2022Multimodal Learning with Transformers: A Surveycited by 400
7 more
  1. 2019D2-Net: A Trainable CNN for Joint Detection and Description of Local Featurescited by 326
  2. 2017Working hard to know your neighbor's margins: Local descriptor learning losscited by 212
  3. 2022DKM: Dense Kernelized Feature Matching for Geometry Estimationcited by 177
  4. 2023ALIKED: A Lighter Keypoint and Descriptor Extraction Network via Deformable Transformationcited by 121
  5. 2019Key.Net: Keypoint Detection by Handcrafted and Learned CNN Filterscited by 118
  6. 2020AdaLAM: Revisiting Handcrafted Outlier Detectioncited by 14
  7. 2020Deep Image Orientation Angle Detectioncited by 5

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