Comments (1)
It's a great question. To be honest we did not detail this part in our preliminary workshop paper. So we are preparing an extended and complete version to speak about the generalization ability of our TEED.
To give you a sneak peek, DoubleFusion help in the generalization capability using the supervised procedure with the aim of weak-supervision process because TEED is not designed to beat the dataset used for training but any downstream task of edge detection.
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Related Issues (20)
- this code is not run HOT 3
- import dataset error HOT 9
- Application scenarios for edge images HOT 1
- sizes not match HOT 2
- Evaluation ODS/OIS/AP HOT 1
- Sketch recognition, JPG to MAT file HOT 9
- The setting problem of TEED training parameters HOT 2
- Why are your edge maps finer HOT 1
- is that possible to use onnx? HOT 3
- Some problem of training process
- When I run main.py, it tells me that I don't have utils.AF, where should I find that file or the library HOT 1
- What are the meanings of each of the 8 models given in the document? HOT 1
- Can i extract xy coordinates of detected edge? HOT 1
- Hello, have you ever tried to reason with openvino or libtorch?
- Fine-tuning TEED Model with Custom Dataset for Diverse Object Outlines HOT 1
- I found out that the train_pair0.lst file and BIPED don't match. HOT 1
- BIPED datase HOT 2
- evaluation
- evaluation HOT 14
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