Comments (6)
I was try to combine this model with onet in MTCNN to detect face and landmarks, it works well.
from faceboxes-tensorflow.
How to combine onet with faceboxes?use faceboxes's prediction as onet's input?
from faceboxes-tensorflow.
Yes. But, change it to a multi task network and retrain it may be better.
from faceboxes-tensorflow.
But the feature map generated by faceboxes is not reused, so may hurt the runtime efficiency?
Also, did you reproduce the performance described in the original paper?
from faceboxes-tensorflow.
Yep.
No, I haven't retrained yet.
from faceboxes-tensorflow.
Hi.
It is a good idea to use onet
with FaceBoxes to detect facial landmarks.
But you could also train a simple keypoint detector by yourself.
Here is an example of training a simple and fast (~0.5 ms on GTX 1080) 5-keypoints detector:
https://github.com/TropComplique/wing-loss (it is not completely finished yet).
It is an implementation of this: https://arxiv.org/abs/1711.06753.
I believe that it will be hard to train FaceBoxes for keypoint prediction using multitask loss.
Because we will need a lot of training data:
images with a lot of face bounding boxes
+ keypoints for each face
.
But we only have data like this:
images with only one face and keypoints for it
. For example, CelebA dataset.
And this:
images with a lot of face bounding boxes only
. For example, WIDER dataset.
And I believe onet
is trained on face crops only. I mean, it sees only close face regions during training.
from faceboxes-tensorflow.
Related Issues (20)
- Understanding ops under reshaping scope HOT 1
- Understanding unnormalized_height and unnormalized_width HOT 2
- why x = 128? HOT 3
- About preprocess
- about the advice of small face HOT 1
- About the picture HOT 2
- Issues running the save.py file HOT 2
- any suggest on Incremental training? HOT 1
- Quantize the model HOT 1
- 你好模型能分享到百度网盘吗? HOT 1
- Check whether your GraphDef-interpreting binary is up to date with your GraphDef-generating binary. HOT 2
- NMS after inference
- problem of running train.py HOT 1
- ValueError: No op named NonMaxSuppressionV3 in defined operations. my tf is 1.6
- Tutorial HOT 2
- How to prepare my dataset? HOT 1
- migrate to tensorflow 2.0?
- Understanding inference
- Understanding NMS from the frozen graph
- Inference Problem
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from faceboxes-tensorflow.