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Code of “Robust Model Reasoning and Fitting via Dual Sparsity Pursuit” NeurIPS 2023 (Spotlight)

Requirements

Successfully test with Matlab 2016b!

VLFeat: https://www.vlfeat.org/ （if vlfeat is not workable, please download then decompress it into subfun/）

Run the Code

for exact model fitting via DSP

Test for two-view geometric model (H or F):

run Demo4KnownModel.m

for unknown model reasoning

Test for 2D point data:

run Demo4point.m

Test for two-view data:

run Demo4UnknownModel.m

Method Description

Illustration of sparse subspace recovery:

image

Data Embedding of Existing Methods and our DSP:

image

Results

Unknown model reasoning results:

qualitative result quantitative result

Exact model fitting results:

[hard datasets]

image

[easy datasets]

image

Citation

Please kindly cite this paper if you use the code in this repository as part of a published research project.

Jiang Xingyu, Ma Jiayi. Robust Model Reasoning and Fitting via Dual Sparsity Pursuit. NeurIPS 2023

 @inproceedings{jiang2023dsp,
	title={Robust Model Reasoning and Fitting via Dual Sparsity Pursuit},
	author={Jiang Xingyu, Ma Jiayi},
        booktitle={Advances in Neural Information Processing Systems},
	year={2023}
}

dsp's People

Contributors

starainj avatar

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