(not issue, sharing) generalized visual quality optimzation (updating ...)

[yuedajiong]

updating ... (I will close or delete this issue once I stop updating)
Your feedback is welcomed as I acknowledge my limitations.

Current topic, 'generalized visual quality':

1. Once you have identified the main challenges of your paper (such as single-view/image, camera-pose-free, dynamic, ...), or once you intend to offer the reconstructed/generated output as a commercial product, you will immediately encounter the primary issue of "generalized visual quality." (SO FAR, NO PAPER CAN DO. JUST TOY OR BIGGER TOY.)
2. Therefore, I am leveraging my limited understanding to attempt an analysis of all the technical aspects related to "generalized visual quality" and gathering relevant papers.

https://github.com/yuedajiong/super-ai/blob/main/superai-20240428-superv-visual-quality.txt

Next topic, I will focus on 'fucking limited resource':

1. single beggar's GPU for train and infer (dataset: objvase-level 3d objects + internet-level 2d images)
2. diff hash based priori (incremental)
3. diff compressed GS respresentation
4. pre-computed image features (eg. features on rendered objvase )
5. ...

https://github.com/yuedajiong/super-ai/blob/main/superai-20240428-superv-limited-resource.txt

[eltitano]

What is going on here?