Comments (1)
The predicted language feature image is the 512 dim language picture. To visualize the result, I selected 3 channels as RGB.
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Related Issues (20)
- Preprocess Error HOT 3
- How can we evaluate the lerf segmentation and localization results as you mentioned in your paper? HOT 1
- poor results on teamtime HOT 12
- different effects between Fig1 in the paper and the video demo on the website
- Can you provide the download link of lerf_ovs HOT 1
- Interface to query gaussian by text in 3d_ovs dataset HOT 2
- 文本查询的演示程序
- Quite poor rendering and eval result! Why! HOT 1
- Failed to build diff_gaussian_rasterization ERROR: Could not build wheels for diff_gaussian_rasterization, which is required to install pyproject.toml-based projects HOT 3
- Concerns about Dataset Usage and Discrepancies in Experimental Results HOT 4
- Cannot Run the training code. HOT 2
- could you update a new version of rasterizer that can render depth
- ValueError: 没有设置language feature HOT 1
- got an unexpected keyword argument 'include_feature' HOT 1
- On the issue of semantic mask segmentation in data processing.
- Problems encountered when processing my own scene HOT 1
- About "lerf_ovs/label the gt_foder"
- How to visualize 3D segmentation results like LERF?
- How to segmentated object only save and rendering?
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