Jianyuan Wang

Hi thanks! Increasing query_frame_num (e.g., 10, 20, or higher) and max_query_pts (e.g., 4096) should help improve robustness, though with a slight trade-off in speed. Regarding the comparison to vggt_to_colmap.py, I’m...

Please check: https://github.com/facebookresearch/vggt/issues/37

Hi may I ask is this useful? https://github.com/facebookresearch/vggt/issues/32

Hi, We just fed two frames into the network, together with query points. The query points are the keypoints from ALIKED.

Hi @GuangyuWang99 , Can you check such a script? ``` import torch from vggt.models.vggt import VGGT from vggt.utils.load_fn import load_and_preprocess_images from vggt.utils.pose_enc import pose_encoding_to_extri_intri from vggt.utils.geometry import unproject_depth_map_to_point_map print("Initializing and...

Hi yes dropping some points may change the scale, while usually random dropping will only make a very small change, e.g., from 1.7863 to 1.7861. I am not sure if...

Hi, Thanks for your kind words! To be honest, I haven’t conducted a thorough theoretical analysis on the efficiency differences. I mainly tested various baselines and reported the empirical numbers....

Hi @kabouzeid , Thanks for your trial. I think the publicly released checkpoint only used: ``` Co3Dv2 BlendMVS DL3DV MegaDepth Kubric WildRGB ScanNet HyperSim Mapillary Taskonomy Habitat Replica MVS-Synth Virtual...

@kabouzeid Thanks a lot and glad to hear this! I’ve linked your GitHub account and this issue in the Readme with the recent commit. If you have an official GitHub...

As suggested by @Nik-V9, in case it’s helpful to others: We used the Mapillary Metropolis dataset, instead of MPSD. Mapillary Metropolis link: https://www.mapillary.com/dataset/metropolis