-
This code has been working great for me. Currently, the discriminative regularization in this codebase uses the loss from the batch norm layers of the ConvolutionalSequence, but the paper covers the m…
-
From the set of definitions stored in the wikipedia articles this module should create a the correspondent pattern instances that will be used to train the discriminative classificators
-
# L2-constrained Softmax Loss for Discriminative Face Verification #
- Author: Rajeev Ranjan, Carlos D. Castillo, Rama Chellappa
- Origin: https://arxiv.org/abs/1703.09507v2
- Related:
-
**Description:**
I would like to propose the addition of a new loss function and detector to the pytorch-ood library: an Angular Loss function (e.g., ArcFace) and an Angle-Based Detector. These add…
-
## 🚀 Feature
Adding support for Additive Angular margin loss to PyTorch as described by *Deng et.al* in *ArcFace: Additive Angular Margin Loss for Deep Face Recognition*
## Motivation
Additive …
-
When the training finished, how does the model give a new sentence a probability?
-
# Reference
- [ ] [paper - 2017 - Semantic Instance Segmentation with a Discriminative Loss Function]()
- [ ] [Github repo](https://github.com/Wizaron/instance-segmentation-pytorch)
-
gradientMex.cpp
D:\visual object tracking\Discriminative Correlation Filter with Channel and Spatial
Reliability\csr-dcf-master\mex_src\hog\gradientMex.cpp(329): error C2664: “int mxSetDimensions_73…
-
I just run
Neural-Dialogue-Generation/Adversarial/discriminative$ th train_dis.lua
-
Some files are missing from your code：In RandomWalkSSA.m，102 lines ‘RA = Random_walk_around_position(dim,Max_iter,lb, ub,X(1,:),i);‘ lack Random_walk_around_position，Please update the file. thanks.
…