Comments (2)
DeAOT/AOT supports using multiple reference frames during inference. The method is simple. You can place all the inference frames in the mask folder. During the inference, the algorithm will paste the reference frame to the predicted mask and cover your prediction.
I designed this function since, in some videos, some objects may not appear in the first frame but in one of the middle frames.
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I designed this function since, in some videos, some objects may not appear in the first frame but in one of the middle frames.
@z-x-yang What about if the optimal reference frame is not frame 0? I see that the evaluator it is strictly forward only and it assume frame 0 reference frame.
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Related Issues (20)
- about DMAOT details? HOT 8
- [Reproducing quantitative numbers of AOT and DeAOT] HOT 7
- YoutubeVOS quantitative numbers
- Object merging in tracking HOT 3
- Recreating the general examples HOT 2
- Optimizing Model Performance: Exploring ONNX Export and Engine Integration with TensorRT and OpenVino HOT 3
- Work Around for Pytorch-Correlation-extension HOT 5
- Demo.py with more then one GPU HOT 2
- package specified for utils HOT 1
- AUX loss WEIGHT and RATIO HOT 3
- [PAOT] swinv2b
- Evaluator Memory
- F.interpolate upsample gradient with amp HOT 1
- SDPA Attention
- How to train aot? Where is aot's train.py?
- Static image
- INT_MAX `local2global`
- How to reproduce the pre_dav_ytb result?
- To feed truth values into the model during the testing phase? HOT 4
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