# CSE5519 Advances in Computer Vision (Topic G: 2023: Correspondence Estimation and Structure from Motion)

## Detector-Free Structure from Motion

[link to paper](https://arxiv.org/abs/2306.15669)

- A new detector-free SfM framework built upon detector-free matchers to handle texture-pool scenes.
- An iterative refinement pipeline with a transformer-based multi-view matching network to efficiently refine both feature tracks and reconstruction results.
  - Multi-view Feature transformer to enhance the discrimitiveness of extracted features.
  - Use Bundle adjustment (view point consistency)
  - Use Topology adjustment (merge, complete, or remove vertices using pre defined rules)

> [!TIP]
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> This paper proposed a new detector-free SfM framework built upon detector-free matchers to handle texture-pool scenes and use an iterative refinement pipeline with a transformer-based multi-view matching network to efficiently refine both feature tracks and reconstruction results.
> 
> I'm particularly interested in the detector-free matchers and the transformer-based multi-view matching network. Due to time constraints, I don't have much time to check the work for detector-free matchers and how they generate the coarse model for predicted matches. I'm looking forward to hearing more about this topic in tomorrow's presentation.