Comments (14)
I am developing a new algorithm that can be used as a supplement to any video frame synthesis algorithm. For example, it can be used to repair bad frames generated by RIFE. It is expected to be released in three months.
from practical-rife.
v4.6 can produce sharp and accurate results, but it's not usable for some kind of footage. So you may want to try older models.
For panning shots, v4.1 often works better.
For footage with patterns (nets/grass/fences/etc.), v4.0 has a better 2D pattern resilience than any other v4.x model including the latest v4.6.
from practical-rife.
I am developing a new algorithm that can be used as a supplement to any video frame synthesis algorithm. For example, it can be used to repair bad frames generated by RIFE. It is expected to be released in three months.
That sounds very interesting!
Looking forward to that
Please do update us with more details if you can in the future and happy holidays!
from practical-rife.
@Q8sh2ing https://drive.google.com/drive/folders/1lPdn7VqT-8dMG5YfXxz9zIGuBBBJKIcg?usp=sharing
from practical-rife.
v2.3 model is unexpectedly good. v4.0 achieves both effects and performance; according to the latest large-scale evaluation report, v4.0 should be a suitable choice
from practical-rife.
Version 4 really has better quality and good performance, but it still falls short of the reference 2.3
from practical-rife.
Version 4 really has better quality and good performance, but it still falls short of the reference 2.3
May I also know the direction for future development?
I saw you added a depth map in the RIFE repo, does this mean RIFE will soon have an awareness to depth as an attempt in increasing the quality? And is it true that you will be implementing multi-frame input to improve quality as well?
from practical-rife.
Version 4 really has better quality and good performance, but it still falls short of the reference 2.3
Where can i get the v4 and v2.3 model?
from practical-rife.
@Q8sh2ing
https://github.com/hzwer/Practical-RIFE#usage and hzwer/ECCV2022-RIFE#41
from practical-rife.
@Q8sh2ing
https://github.com/hzwer/Practical-RIFE#usage and hzwer/ECCV2022-RIFE#41
Thanks, I can't believe i miss that...
from practical-rife.
@hzwer
Sidenote
Is training for RIFE still ongoing? And are the plans you outlined previously like taking multi frame input still being worked on?
from practical-rife.
from practical-rife.
https://drive.google.com/drive/folders/11u79nnOagqzo5cqza9myh--TCyg6OLBn
These are the input and outputs when testing out different models, do yall get the same result? v4 models seems to produce a lot of distortion, I mean the results are pretty accurate but the distortions are just out of topic.
from practical-rife.
For footage with patterns (nets/grass/fences/etc.), v4.0 has a better 2D pattern resilience than any other v4.x model including the latest v4.6.
I hope there is more focus on this case in future models, as these artifacts are very noticeable and distracting, and most live action content at least will have a scene that triggers the issue.
from practical-rife.
Related Issues (20)
- Rife v4.14 lite HOT 6
- model.update中的loss_cons相关问题 HOT 1
- import nori2 as nori HOT 1
- Do you have charted out performance of different models HOT 4
- Nothing work "model no defined"
- He cant find ffmpeg HOT 2
- Video Freeze after Frame Interpolation
- 训练问题 HOT 2
- ONNX export script HOT 2
- Model Training HOT 4
- Practical RIFE vs ECCV2022 RIFE teacher differences HOT 4
- FFMPEG arguments? HOT 2
- Absence of refinenet in training scripts HOT 2
- Deeper guide for arguments HOT 2
- Will there be another Rife model? HOT 12
- Request to incorporate InterpAny-Clearer's technology in Practical-RIFE HOT 4
- 可否增加rife v4.17 lite? HOT 2
- How to avoid RIFE from Re-encoding output to MPEG codec HOT 1
- Torch_TensorRT inference? HOT 1
- Core dump *after* processing is done
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