Outputs (2)

Using outlier elimination to assess learning-based correspondence matching methods (2024)
Journal Article
Ding, X., Luo, Y., Jie, B., Li, Q., & Cheng, Y. (2024). Using outlier elimination to assess learning-based correspondence matching methods. Information Sciences, 659, Article 120056. https://doi.org/10.1016/j.ins.2023.120056

Recently, deep learning (DL) technology has been widely used in correspondence matching. The learning-based models are usually trained on benign image pairs with partial overlaps. Since DL model is usually data-dependent, non-overlapping images may b... Read More about Using outlier elimination to assess learning-based correspondence matching methods.

NeuFG: Neural Fuzzy Geometric Representation for 3D Reconstruction (2024)
Journal Article
Hong, Q., Yang, C., Chen, J., Li, Z., Wu, Q., Li, Q., & Tian, J. (2024). NeuFG: Neural Fuzzy Geometric Representation for 3D Reconstruction. IEEE Transactions on Fuzzy Systems, https://doi.org/10.1109/TFUZZ.2024.3447088

3D reconstruction from multi-view images is considered as a longstanding problem in computer vision and graphics. In order to achieve high-fidelity geometry and appearance of 3D scenes, this paper proposes a novel geometric object learning method for... Read More about NeuFG: Neural Fuzzy Geometric Representation for 3D Reconstruction.