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README.md

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 (GAIIC) giga-rendering: giga-pixel novel view synthesis competition 4th place solution. Implementation based on [nerfstudio](https://github.com/nerfstudio-project/nerfstudio). The other two contributors are [Dinnger](https://github.com/Dinngger) and [funnymudpeer](https://github.com/funnymudpeer).
 
 The ranks can be found in [giga-vision's leaderboard for rendering challenge](https://gigavision.cn/track/track?nav=Sparse%20rendering&type=nav). Our presentation slides can be found [here](https://docs.google.com/presentation/d/16zcceAIQLTjLUsLQfgxJlnt-Mq_6Hl5w/edit?usp=sharing&ouid=113113092240480704238&rtpof=true&sd=true) 
-![Screenshot 2023-06-19 111113](https://github.com/Enigmatisms/nerfstudio-giga/assets/46109954/a9b36352-49b2-4bec-8167-a7283beca0c7)
+![Screenshot 2023-06-19 111113](https://github.com/Enigmatisms/nerfstudio-giga/assets/46109954/240cb6e5-765b-4a4c-82a2-194e2e1a7a40)
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 #### Part of the results
 
 DayaTemple trained for 10min:
 
-https://github.com/Enigmatisms/nerfstudio-giga/assets/46109954/8c188691-bdf0-487c-8ebc-f7e50b2c571b
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+https://github.com/Enigmatisms/nerfstudio-giga/assets/46109954/ce904944-4854-4e44-b5d4-23f7bc74f9ca
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 ScienceSquare full model, RGB and depth rendering:
 
-https://github.com/Enigmatisms/nerfstudio-giga/assets/46109954/ce8ccd3b-6bfd-4b6c-aa1c-b6d66d36cd78
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+https://github.com/Enigmatisms/nerfstudio-giga/assets/46109954/ed175a46-6fe5-4a0a-ae6c-6f6b3f935555
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 Memorialhall full model, RGB and depth rendering:
 
-https://github.com/Enigmatisms/nerfstudio-giga/assets/46109954/cb8c3c43-5b93-46b6-af53-0ee5f4857866
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+https://github.com/Enigmatisms/nerfstudio-giga/assets/46109954/0ff7ffdc-0edb-4642-9519-e4e63228bf25
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 Detail zoom in (in test views). Our model does aggressive pose optimization and re-estimation, therefore the details are rich:
 
 
-https://github.com/Enigmatisms/nerfstudio-giga/assets/46109954/9a061975-d3d2-4a21-878c-16ad17107da8
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+https://github.com/Enigmatisms/nerfstudio-giga/assets/46109954/590a58af-4de3-4156-8b68-b2cb3eda4bf2
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