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Found 7 papers, 3 papers with code
Authentic Emotion Mapping: Benchmarking Facial Expressions in Real News
In this paper, we present a novel benchmark for Emotion Recognition using facial landmarks extracted from realistic news videos.
AMF: Adaptable Weighting Fusion with Multiple Fine-tuning for Image Classification
Fine-tuning is widely applied in image classification tasks as a transfer learning approach.
Exploring Biases and Prejudice of Facial Synthesis via Semantic Latent Space
Varying the proportions of male and female faces in the training data can have a substantial effect on behavior on the test data: we found that the seemingly obvious choice of 50:50 proportions was not the best for this dataset to reduce biased behavior on female faces, which was 71% unbiased as compared to our top unbiased rate of 84%.
Disentangling Noise from Images: A Flow-Based Image Denoising Neural Network
The prevalent convolutional neural network (CNN) based image denoising methods extract features of images to restore the clean ground truth, achieving high denoising accuracy.
Invertible Denoising Network: A Light Solution for Real Noise Removal
InvDN transforms the noisy input into a low-resolution clean image and a latent representation containing noise.
A Token-wise CNN-based Method for Sentence Compression
Sentence compression is a Natural Language Processing (NLP) task aimed at shortening original sentences and preserving their key information.
Are Deep Neural Architectures Losing Information? Invertibility Is Indispensable
Identifying the information lossless condition for deep neural architectures is important, because tasks such as image restoration require keep the detailed information of the input data as much as possible.
