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Found 16 papers, 7 papers with code
Mushroom Segmentation and 3D Pose Estimation from Point Clouds using Fully Convolutional Geometric Features and Implicit Pose Encoding
We have validated the effectiveness of the proposed implicit-based approach for a synthetic test set, as well as provided qualitative results for a small set of real acquired point clouds with depth sensors.
Best Practices for a Handwritten Text Recognition System
Handwritten text recognition has been developed rapidly in the recent years, following the rise of deep learning and its applications.
3D Facial Expressions through Analysis-by-Neural-Synthesis
Instead, SMIRK replaces the differentiable rendering with a neural rendering module that, given the rendered predicted mesh geometry, and sparsely sampled pixels of the input image, generates a face image.
Feather: An Elegant Solution to Effective DNN Sparsification
Neural Network pruning is an increasingly popular way for producing compact and efficient models, suitable for resource-limited environments, while preserving high performance.
Matrix Factorization in Tropical and Mixed Tropical-Linear Algebras
Matrix Factorization (MF) has found numerous applications in Machine Learning and Data Mining, including collaborative filtering recommendation systems, dimensionality reduction, data visualization, and community detection.
Keyword Spotting Simplified: A Segmentation-Free Approach using Character Counting and CTC re-scoring
Recent advances in segmentation-free keyword spotting treat this problem w. r. t.
On the Matrix Form of the Quaternion Fourier Transform and Quaternion Convolution
We focus especially on the relation of Quaternion Fourier Transform matrices to Quaternion Circulant matrices (representing quaternionic convolution), and the eigenstructure of the latter.
WordStylist: Styled Verbatim Handwritten Text Generation with Latent Diffusion Models
Our proposed method is able to generate realistic word image samples from different writer styles, by using class index styles and text content prompts without the need of adversarial training, writer recognition, or text recognition.
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Visual Speech-Aware Perceptual 3D Facial Expression Reconstruction from Videos
The recent state of the art on monocular 3D face reconstruction from image data has made some impressive advancements, thanks to the advent of Deep Learning.
Trainable Learning Rate
Selecting an appropriate learning rate for efficiently training deep neural networks is a difficult process that can be affected by numerous parameters, such as the dataset, the model architecture or even the batch size.
Tropical Geometrical Zonotope Reduction as Applied to Neural Network Compression.
Based on this result, we propose geometrical neural network compression methods that employ the K-means algorithm.
Enhancing Handwritten Text Recognition with N-gram sequence decomposition and Multitask Learning
In our work, we utilize a Multi-task Learning scheme, training the model to perform decompositions of the target sequence with target units of different granularity, from fine to coarse.
WSRNet: Joint Spotting and Recognition of Handwritten Words
The related joint loss leads to a boost in recognition performance, while the Seq2Seq branch is used to create efficient word representations.
Weight Pruning via Adaptive Sparsity Loss
Pruning neural networks has regained interest in recent years as a means to compress state-of-the-art deep neural networks and enable their deployment on resource-constrained devices.
An Alternative Deep Feature Approach to Line Level Keyword Spotting
Three distinct components, all modeled as neural networks, are combined: normalization, feature extraction and representation of image and textual input into a common space.
RecNets: Channel-wise Recurrent Convolutional Neural Networks
In this paper, we introduce Channel-wise recurrent convolutional neural networks (RecNets), a family of novel, compact neural network architectures for computer vision tasks inspired by recurrent neural networks (RNNs).
