Trying to train with video frames in steps

[lolwarmaze]

Hi there! I have been trying to incorporate the EndoGaussian work in my own project where I am training a scene with left and right image - pairs and depth maps. I am trying to develop a stepwise training method where let's say that first 150 frames are loaded, then trained and then sent for rendering with a custom camera pose in real time. I want to train the next 30 frames by loading the already trained model (trained on first 150 frames) and then train the next 30 frames on it, and then render them as the next step. The pipeline keep training and rendering the next 30 frames in steps till all the available frames in the data folder are trained.

Now comes the problem I am having with this. The rendered frames when converted to the video show a slight inconsistency between the frames where model is changed. So it shows the first 150 frames to have smooth Gaussian movements, then suddenly there is a small abrupt transition to the next frame and then the next 30 frames are smooth. So basically every 30 frames when the model is changed to a newer trained model, there is a noticeable jump in gaussian positions and then for the next 29 frames it will be smooth change in gaussian positions.

So my question is, how can I train the model with new timestamps, by keeping the previously trained timestamps to be unaffected? Because it seems like when training a newer timestamp, the model also adjusts how the positions of gaussians will be affected for previous timestamps. Or is there any other reason for this ? Also is there any other way to train and render stepwise if time cannot be made independent? If someone has any ideas or understanding of it then please help me. Any other suggestions will also be appreciated. Thanks