Open jiangyijin opened 7 months ago
Hi, do you have any idea about this problem now?I constructed my own synthetic dataset in the same way, but the rendered scene was all black and no 3d Gaussians were generated. Do you have any useful improvements to share?
Thank you so much!
Hi, do you have any idea about this problem now?I constructed my own synthetic dataset in the same way, but the rendered scene was all black and no 3d Gaussians were generated. Do you have any useful improvements to share?嗨,你现在对这个问题有什么想法吗?我以同样的方式构建了自己的合成数据集,但渲染的场景全是黑色,没有生成任何 3D 高斯。你有什么有用的改进可以分享吗?
Thank you so much! 非常感谢!
It is recommended to use COLMAP for pose estimation, and then proceed with training.
Hi, do you have any idea about this problem now?I constructed my own synthetic dataset in the same way, but the rendered scene was all black and no 3d Gaussians were generated. Do you have any useful improvements to share?嗨,你现在对这个问题有什么想法吗?我以同样的方式构建了自己的合成数据集,但渲染的场景全是黑色,没有生成任何 3D 高斯。你有什么有用的改进可以分享吗?
Thank you so much! 非常感谢!
And I myself have converted the above posture for training, but the results are not very good. This may be due to the fact that the initial point cloud is random. It may also be that the posture conversion is not accurate, and we are currently investigating the problem.
Hello, I encountered a failure in reconstructing shirtv1 from the speed+ dataset. I first converted the camera.json file and the camera parameters roe2.json file from the dataset into the format required by the nerf dataset, as shown below. { "camera_angle_x": 5.86e-06, "rotation": 3.1415557843472173, "frames": [ { "file_path": "img000001.jpg", "rotation": 3.1415557843472173, "transform_matrix": [ [ 1.0, -1.0206827928449808e-16, 8.85350556627883e-18, 0.04852291750863577 ], [ 2.943923360032076e-17, 0.36904495838715945, 0.9294115443058688, -0.31807457560899577 ], [ -9.813077866773592e-17, -0.9294115443058688, 0.36904495838715945, 7.86837091563897 ], [ 0.0, 0.0, 0.0, 1.0 ] ] }, However, when I attempted the reconstruction using these parameters, the results were very poor, to the extent that there was no visible point cloud. Can someone assist me in resolving this issue? Thank you very much! Below is the specific content of the camera.json file: { "Nu": 1920, "Nv": 1200, "ppx": 5.86E-6, "ppy": 5.86E-6, "fx": 0.017697236438454025, "fy": 0.017697236438454025, "ccx": 960, "ccy": 600, "cameraMatrix": [ [ 3020.0062181662161, 0, 960 ], [ 0, 3020.0062181662161, 600 ], [ 0, 0, 1 ] ], "distCoeffs": [ -0.21249040440358169, 0.4443683447224509, -0.00038703301037756828, -0.00044885973454884538, 0.56835118403785934 ] } Below is the specific content of the roe2.json file: [ { "filename": "img000001.jpg", "q_vbs2tango_true": [ -0.82735873669985494, 0.56167385626039268, -3.2327054604134184E-17, -3.9737149996557807E-17 ], "r_Vo2To_vbs_true": [ 0.048522917508635771, -0.31807457560899577, 7.86837091563897 ] }, { "filename": "img000002.jpg", "q_vbs2tango_true": [ -0.82542466067382414, 0.56363503659809222, -0.011931472870665516, -0.029108676124239254 ], "r_Vo2To_vbs_true": [ 0.051787825059848837, -0.31742644621634647, 7.8671667361472455 ] }, { "filename": "img000003.jpg", "q_vbs2tango_true": [ -0.822602785207585, 0.56512824651642046, -0.024000254897478319, -0.05812667651651994 ], "r_Vo2To_vbs_true": [ 0.055041116890462177, -0.31667209568172283, 7.8658190773001042 ] }, Here is my final reconstruction result. This is a paper on speed+.Adaptive Neural Network-based Unscented Kalman Filter for.pdf
[SIBR] -- INFOS --: Initialization of GLFW [SIBR] -- INFOS --: OpenGL Version: 4.6.0 NVIDIA 551.61[major: 4, minor: 6] [SIBR] -- INFOS --: Did not find specified input folder, loading from model path [SIBR] ## ERROR ##: FILE C:\projects\gauss2\SIBR_viewers\src\core\scene\ParseData.cpp LINE 560, FUNC sibr::ParseData::getParsedData Cannot determine type of dataset at /D:\try_speed+\sunlamp Number of input Images to read: 2511 Number of Cameras set up: 2511 [SIBR] -- INFOS --: Mesh contains: colors: 1, normals: 1, texcoords: 0 [SIBR] -- INFOS --: Mesh 'C:\Users\users\Downloads\result/input.ply successfully loaded. 1 meshes were loaded with a total of (0) faces and (100000) vertices detected. Init GL ... [SIBR] -- INFOS --: Init GL mesh complete [SIBR] -- INFOS --: Loading 299 Gaussian splats [SIBR] -- INFOS --: Initializing Raycaster [SIBR] -- INFOS --: Interactive camera using (0.009,1100) near/far planes. Switched to trackball mode.