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Thanks!
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Thanks for your attention.
- Multi-Reference IDOL samples one key frame and multiple adjacent reference frames as the training sample. For each instance in key frames, we will select the corresponding positive and negative embeddings from all reference frames.
- IDOL with Mask2Former use the Mask2Former as the segementor. For reproducibility, we adopt a similar positive and negative sample assignment pattern as our CTVIS.
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Related Issues (20)
- [Demo] Dance video.
- [Inference Reproduce] The influence of GPU and Pytorch
- how to export in onnx format HOT 1
- request model weight for all benchmarks HOT 1
- how to do online segmentation by using a webcam? HOT 1
- inconsistent contrastive training scheme with paper HOT 2
- visualization of the results
- Real-Time Inference for CTVIS - Performance and Implementation Inquiry
- Register Custom Dataset HOT 5
- Adding new backbone
- A bug in your code HOT 1
- Trying to test a model trained with 8 GPUs on a single GPU HOT 1
- An question on memory bank update with noise HOT 1
- Undefined symbol ImportError
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- Some problems in browse_datasets and training
- Some code issues HOT 5
- Sharing the split for partial training examples HOT 1
- about contrastive learning on VPS HOT 1
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