Comments (1)
Hi, I didn't do strict evaluations on the effect of video length. The longest video I trained was 9mins (about 11000 frames) and the shortest was 2mins (about 2500 frames). As expected, more video frames lead to better results. And for the result of 2 mins video, there were obvious artifacts (especially in the boundary between head and torso).
It's great that you are kind to do the evaluation and that will be very helpful. Thanks!
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Related Issues (20)
- Tool(s) to adjust or replace the default head mesh (missing?)
- KeyError: "The name 'deepspeech/logits:0' refers to a Tensor which does not exist. The operation, 'deepspeech/logits', does not exist in the graph." HOT 1
- ValueError: Got non-broadcastable sizes [1, 1, 1, 1, 0, 0], c = tensor([], device='cuda:0', size=(0, 3, 3)) HOT 1
- RTX3060 合成一帧要 24 秒,合成 300 帧需要 2 小时,这正常吗 HOT 2
- Basel Face Model substitute HOT 1
- replacing the deepspeech code HOT 1
- Training loss and PSNR unstable , test output only background?
- 已创建生成逼真的数字人讨论组,需要交流的请加我微信 wav2lip
- wav2Vec instead of deepspeech since deepspeech no longer maintained?
- How corp the images from videos
- step 2, error HOT 1
- Do I just have to run the torsoNeRF for the test for rendering? HOT 3
- 2023-09-17 21:17:40.944285: E tensorflow/stream_executor/cuda/cuda_blas.cc:428] failed to run cuBLAS routine: CUBLAS_STATUS_EXECUTION_FAILED
- 输出视频 HOT 3
- Does someone knows why the confidence I measured for lipsync is only 0.something?
- 关于deepspeech_fps = 50和video_fps = 50的问题
- 卡在了处理数据上,请问有处理好数据吗
- Train/test protocol
- 指标评估
- Lip Sync result HOT 3
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