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inCyberAgentAILab/SuperNormal (press backspace or delete to remove)

In case anybody has issue with dependencies. I created a dockerfile for your convenience. FROM nvidia/cuda:11.8.0-cudnn8-devel-ubuntu18.04 ENV DEBIAN_FRONTEND noninteractive # Install basic dependencies ...
  • iernstig
  • Opened 
    16 days ago
  • #12

Thanks for opening source such great work! I found that the code uses a same way as idr to handle perspective projection. What modifications need to be made to adapt to orthogonal projection? In addition, ...
  • l1346792580123
  • 2
  • Opened 
    on Dec 11, 2024
  • #11

Hi, I m using XHumans Dataset which provide mesh. I rendered normal with camera poses and got error as following while training the model. Any insight would be helpful. true_normal torch.Size([2048, 3, ...
  • gwang-kim
  • 6
  • Opened 
    on Sep 6, 2024
  • #10

https://github.com/CyberAgentAILab/SuperNormal/blob/9dce99ce0eff24d63da022c7e8ebc95766168d44/models/dataset_loader.py#L35 Hi, Thanks for your great work and code! I find a annotation typo here. It seems ...
  • Binyr
  • Opened 
    on Aug 20, 2024
  • #9

the code is not loading the checkpoint correctly. since its only loading the state_dict, attributes like the the bandwidth are not correctly loaded.
  • therealron
  • Opened 
    on Jul 12, 2024
  • #8

Hi, Could you provide some information about reconstruct on custom data? And how to get normal maps? Thanks very much.
  • YiChenCityU
  • 3
  • Opened 
    on May 11, 2024
  • #7

Hi, Thank you for the work and the code! When I tried to run the DiLiGenT-MV benchmark objects, it seems that the final saving requires very large memory: img width= 986 alt= 129deddcfea7e2e8140b56f12d5c1c2 ...
  • MickShen7558
  • 1
  • Opened 
    on Apr 26, 2024
  • #6

Hi, great work! In the data, how is the scale_mat calculated? It is used to bring the points in the unit sphere to world coordinates so that we can project them into the camera using the world_mat, right? ...
  • therealron
  • 3
  • Opened 
    on Apr 18, 2024
  • #5
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