novel view synthesis quality with a self-collected dataset of different moving specular objects in realistic environments. The experimental results demonstrate that our method significantly improves the reconstruction quality of moving specular objects from monocular RGB videos compared to the existing NeRF ...
in two main stages: one that encodes the scene into a canonical space and another that maps this canonical representation into the deformed scene at a particular time. Both mappings are simultaneously learned using fully-connected networks. Once the networks are trained, D-NeRF can render novel i...
Each NeRF model was then evaluated on its ability to reconstruct scenes and synthesize novel views based on different subsets of the dataset. Accordingly, we found EmerNeRF consistently and significantly outperformed other methods in both scene reconstruction and novel view synthesis, as shown in Table...
We obtain the results of NSFF and NR NeRF using the official implementation with default parameters. Train a model on your sequence Set some paths ROOT_PATH=/path/to/the/DynamicNeRF/folder DATASET_NAME=name_of_the_video_without_extension DATASET_PATH=$ROOT_PATH/data/$DATASET_NAME ...
Quantitative comparison on D-NeRF datasets. We present the average PSNR/SSIM/LPIPS (VGG) values for novel view synthesis on dynamic scenes from D-NeRF, with each cell colored to indicate the best, second best, and third best. Dataset
Official repository for"Sync-NeRF: Generalizing Dynamic NeRFs to Unsynchronized Videos" enabling dynamic NeRFs to successfully reconstruct the scene from unsynchronized dataset. Setup We provide an integrated requirements file for Sync-MixVoxels and Sync-K-Planes. ...
For videos run: python scripts/colmap2nerf.py --run_colmap --from_video --colmap_matcher sequential --video_fps 5 --dir data/[folder_name] Train NeRF Run python3 train.py --model_type tensorf --data_dir data/[dataset_name] Contributors2...
Dynamic Neural Radiance Field (NeRF) from monocular videos has recently been explored for space-time novel view synthesis and achieved excellent results. However, defocus blur caused by depth variation often occurs in video capture, compromising the quality of dynamic reconstruction because the lack of...
1.在Dynamic Scene dataset的camera pose estimation上比Dynamic NeRF文章略有优势;而且作者的method没用COLMAP的pose来初始化。且恢复的scene geometry和detail较好 2.在iPhonedataset的NVS任务上和其他文章没有明显优势(这个有没有人解释一下原因?) 3.DAVIS dataset数据集上,同时使用作者method得到的camera pose情况下...
随后,将条件 3D 高斯投影到 2D splat。 最后,我们整合平面条件高斯、一维边缘高斯和随时间演化的视图相关颜色来渲染视图 I。 实验 数据集:Plenoptic Video dataset,D-NeRF Plenoptic Video benchmark D-NeRF dataset 消融实验编辑于 2024-04-28 16:22・浙江...