Question about Background Object Stationarity & Poor Natural Image Inference Quality
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Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 35/100
- Issue type
- Bug
- Clarity
- Needs clarification
- Activity status
- Quiet
- Tech stack
- python
- Domain
- machine-learning
Research direction
Start by reproducing the inference behavior with the three attached natural-image examples and compare the reported stationary-background and runner results. Determine whether the observed behavior is an inference defect or an unsupported input scenario; done means the behavior and supported application scope are clearly established.
Written by the indexing model from the issue text.
Description
I hope to confirm whether background objects are designed to be recognized as stationary by default. For example, in a road scene featuring a person running, the inference result appears to indicate that the runner is stationary, which seems inconsistent with the actual motion state.
Additionally, I would like to ask if the application scenario of this project is restricted to the Minecraft game environment? I have attempted to conduct inference on natural images, but the quality of the resulting images is unfortunately quite poor.
To help with troubleshooting, I have attached three test examples of my own for your reference.
https://github.com/user-attachments/assets/95c93135-cf70-452d-8fc6-abdaffda524e
https://github.com/user-attachments/assets/c0a86e2c-e9e1-4f9a-869a-7ba975a7dfc2
https://github.com/user-attachments/assets/d3efc4fe-8d08-4e09-bef1-d7f0a8446003
- Dominant language
- Python
- Stars
- 2.3k
- Forks
- 254
- PR merge metrics
- No merged PRs in 30d
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
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