2D-3D Match Dataset 是一个通过利用来自 RGB-D 扫描的几个 3D 数据集实现 2D-3D 对应的数据集。数据集使用来自 SceneNN 和 3DMatch 的数据。训练数据集由 110 个 RGB-D 扫描组成，其中 56 个场景来自 SceneNN，54 个场景来自 3DMatch，给定从 3D 点云随机采样的 3D 点，从不同扫描视图中提取一组 3D 补丁。该数据集采用一种学习局部跨域描述符的新方法，以用于二维图像和三维点云匹配。数据集包含从公开的 RGB-D 场景中获得 140 万个具有不同照明条件和设置的 2D-3D 对应关系

Citation

If you find our work useful for your research, please consider citing: @inproceedings{pham2020lcd, title = {{LCD}: {L}earned cross-domain descriptors for 2{D}-3{D} matching}, author = {Pham, Quang-Hieu and Uy, Mikaela Angelina and Hua, Binh-Son and Nguyen, Duc Thanh and Roig, Gemma and Yeung, Sai-Kit}, booktitle = {AAAI Conference on Artificial Intelligence}, year = 2020 } @inproceedings{hua2016scenenn, title = {{SceneNN}: {A} scene meshes dataset with a{NN}otations}, author = {Hua, Binh-Son, and Pham, Quang-Hieu and Nguyen, Duc Thanh and Tran, Minh-Khoi and Yu, Lap-Fai and Yeung, Sai-Kit}, booktitle = {International Conference on 3D Vision}, year = 2016 } @inproceedings{zeng20173dmatch, title = {{3DMatch}: {L}earning local geometric descriptors from {RGB}-{D} reconstructions}, author= {Zeng, Andy and Song, Shuran and Nie{\ss}ner, Matthias and Fisher, Matthew and Xiao, Jianxiong and Funkhouser, Thomas}, booktitle = {IEEE Conference on Computer Vision and Pattern Recognition}, year = 2017 }