Comments (1)
Hi. I think there are two ways to achieve your goal. The first one is that train spatial LoRAs on the initial image, combining with the temporal LoRAs learned from reference videos. The second one is that you can try to use the inversion noise from the initial image to denoise and generate videos.
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Related Issues (20)
- Errors in Lora : UnboundLocalError: local variable '_tmp' referenced before assignment` HOT 2
- Training the example code but Crashed HOT 2
- Testing samples HOT 1
- pickle.UnpicklingError: invalid load key, 'v'. HOT 1
- Some confusion about the inconsistency between code and paper description HOT 4
- training time HOT 1
- How to fix random seed? HOT 1
- Why are the inference results different from the results you posted? HOT 5
- May I ask what work the lora-related code(eg.class LoraHandler) is based on? HOT 1
- earlier checkpoints doing better than later checkpoints HOT 2
- Does every new animation need to be retrained? HOT 1
- Adding more data in the test folder . HOT 1
- Why can't I reproduce the beautiful results shown by the author even using the weight file provided by the author on huggingface HOT 1
- About the training parameters of Spatial Lora: Recursive ones? HOT 1
- Request for Benchmark Datasets used in MotionDirector HOT 1
- support cogvideox? HOT 2
- How to use MotionDirector to train a LoRA based on other base models? HOT 1
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- Ideal number of videos
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