并且基于高效注意力机制的分层 ViTs的微调MVSFormer可以在FPNs的基础上实现显著的提高。 其他贡献: 1.提出具有冻结ViT权重的MVSFormer,在很大程度上缓解了训练成本,并通过自蒸馏预训练的注意力图增强了竞争性能; 2.MVSFormer通过梯度积累加强的高效多尺度训练,可以泛化多种输入分辨率; 3.讨论了基于分类和回归的MVS方法...
核心思想:继MVSFormer使用Transformer进行特征提取之后,MVSFormer++提出在MVS的各个部分中继续深入探讨Transformer的作用。主要分为以下几点: 1.该方法包括将交叉视图信息注入预训练的DINOv2模型中,以促进MVS学习; 2.对特征编码器和代价体正则化采用了不同的注意力机制,分别关注特征和空间聚合; 3.发现一些设计细节会实质...
MVSFormer-P (frozen DINO-based). CUDA_VISIBLE_DEVICES=0,1 python train.py --config configs/config_mvsformer-p.json \ --exp_name MVSFormer-p \ --data_path ${YOUR_DTU_PATH} \ --DDP We should finetune our model based on BlendedMVS before the testing on T&T. CUDA_VISIBLE_DEVICES=...
Edge_MVSFormer was pre-trained on two public MVS datasets and fine-tuned with our private data of 10 model plants collected for this study. Experimental results on 10 test model plants demonstrated that for depth images, the proposed algorithm reduces the edge error and overall reconstruction ...
MVS Hosts Horticulture Society ; Former Ohio First Lady Sees Lab/ GreenhouseMcGinnis, Pam
Codes of MVSFormer++: Revealing the Devil in Transformer’s Details for Multi-View Stereo (ICLR2024) - maybeLx/MVSFormerPlusPlus
Codes of MVSFormer++: Revealing the Devil in Transformer’s Details for Multi-View Stereo (ICLR2024) - MVSFormerPlusPlus/requirements.txt at main · maybeLx/MVSFormerPlusPlus
MVSFormer-P (frozen DINO-based). CUDA_VISIBLE_DEVICES=0,1 python train.py --config configs/config_mvsformer-p.json \ --exp_name MVSFormer-p \ --data_path ${YOUR_DTU_PATH} \ --DDP We should finetune our model based on BlendedMVS before the testing on T&T. CUDA_VISIBLE_DEVICES=...